Dissertations / Theses on the topic 'Evolutionary models'
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Hall, Matt. "Models of evolutionary ecology." Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268796.
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Hartmann, Klaas. "Biodiversity conservation and evolutionary models." Thesis, University of Canterbury. Mathematics and Statistics, 2008. http://hdl.handle.net/10092/1776.
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Biodiversity conservation requires a framework for prioritising limited resources to the many endangered species. One such framework that has seen much attention and is considered extensively in this thesis, is the Noah's Ark Problem (NAP). The NAP combines a biodiversity measure (Phylogenetic Diversity; PD) with species survival probabilities and conservation costs. The aim of the NAP is to allocate the limited conservation resources such that the future expected PD is maximised. Obtaining optimal solutions to the NAP is a computationally complex problem to which several efficient algorithms are provided here. An extension to the NAP is also developed which allows uncertainty about the survival probability estimates to be included. Using this extension we show that the NAP is robust to uncertainty in these parameters and that even very poor estimates are beneficial. To justify using or promoting PD, it must produce a significant increase in the amount of biodiversity that is preserved. We show that the increase attainable from the NAP is typically around 20% but may be as high as 150%. An alternative approach to PD and the NAP is to prioritise species using simple species specific indices. The benefit of these indices is that they are easy to calculate, explain and integrate into existing management frameworks. Here we investigate the use of such indices and show that they provide between 60% and 80% of the gains obtainable using PD. To explore the expected behaviours of conservation methods (such as the NAP) a distribution of phylogenetics trees is required. Evolutionary models describe the diversification process by which a single species gives rise to multiple species. Such models induce a probability distribution on trees and can therefore be used to investigate the expected behaviour of conservation methods. Even simple and widely used models, such as the Yule model, remain poorly understood. In this thesis we present some new analytic results and methods for sampling trees from a broad range of evolutionary models. Lastly we introduce a new model that provides a simple biological explanation for a long standing discrepancy between models and trees derived from real data -- the tree balance distribution.
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Forrester, Deanna L., and University of Lethbridge Faculty of Arts and Science. "Evolutionary models for male androphilia." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Psychology, 2011, 2011. http://hdl.handle.net/10133/2631.
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Androphilia refers to sexual attraction and arousal to adult males, whereas gynephilia
refers to sexual attraction and arousal to adult females. Prehistoric artifacts such as art
and pottery indicate that male-male same sex behaviour has existed for millennia.
Bearing this in mind, and considering that male androphilia has a genetic component yet
androphilic males reproduce at a fraction of the rate than do gynephilic males, how the
genes for male androphilia have been maintained in the population presents an
evolutionary puzzle. This thesis tests two hypotheses that attempt to address this
Darwinian paradox. Chapter one reviews the current literature on the kin selection
hypothesis and the sexually antagonistic gene hypothesis. In addition, rationales for
testing these hypotheses in Canada are provided. Chapter two tests the kin selection
hypothesis for male androphilia within a Canadian population. Results and implications
are discussed. Chapter three tests the sexually antagonistic gene hypothesis within a
Canadian population. Results and implications are discussed. Chapter four summarizes
the results of the two studies and discusses how these findings may be interpreted from
an evolutionary perspective. The impacts of gene-environment interaction on the
functional behavioral expression of traits are emphasized.viii, 113 leaves ; 29 cm
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Hadjichrysanthou, C. "Evolutionary models in structured populations." Thesis, City University London, 2012. http://openaccess.city.ac.uk/1731/.
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Evolutionary dynamics have been traditionally studied in infinitely large homogeneous populations where each individual is equally likely to interact with every other individual. However, real populations are finite and characterised by complex interactions among individuals. In this work, the influence of the population structure on the outcome of the evolutionary process is explored. Through an analytic approach, this study first examines the stochastic evolutionary game dynamics following the update rules of the invasion process, an adaptation of the Moran process, on finite populations represented by three simple graphs; the complete graph, the circle and the star graph. The exact formulae for the fixation probability and the speed of the evolutionary process under different conditions are derived, and the effect of the population structure on each of these quantities is studied. The research then considers to what extent the change of the strategy update rules of the evolutionary dynamics can affect the evolutionary process in structured populations compared to the process in homogeneous well-mixed populations. As an example, the evolutionary game dynamics on the extreme heterogeneous structure of the star graph is studied analytically under different update rules. It is shown that in contrast to homogeneous populations, the choice of the update rules might be crucial for the evolution of a non-homogeneous population. Although an analytic investigation of the process is possible when the contact structure of the population has a simple form, this is usually infeasible on complex structures and the use of various assumptions and approximations is necessary. This work introduces an effective method for the approximation of the evolutionary process in populations with a complex structure. Another component of this research work involves the use of game theory for the modelling of a very common phenomenon in the natural world. The models developed examine the evolution of kleptoparasitic populations, foraging populations in which animals can steal the prey from other animals for their survival. A basic game-theoretical model of kleptoparasitism in an infinite homogeneous well-mixed population is extended to structured populations represented by different graphs. The features of the population structure that might favour the appearance of kleptoparasitic behaviour among animals are addressed. In addition, a game-theoretical model is proposed for the investigation of the ecological conditions that encourage foraging animals to share their prey, a very common behaviour occurring in a wide range of animal species.
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Clarke, Magnus. "Evolutionary models with ecological interactions." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/19890/.
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Models for the evolution of species' traits and speciation rates usually ignore ecology: most comparative analyses of evolution are ecologically neutral and ignore ecological mechanisms such as competition and limiting similarity. However, such processes can impact profoundly on the distribution of traits across a group of species if they are ecologically similar (e.g. as in adaptive radiations). Here, two new models are introduced to explicitly include the effects of lineage-lineage interactions, one generating trait evolution and the other addressing lineage diversification. The new model for trait evolution is fitted to a wide range of existing animal datasets, using a simulation approach. Evidence was found of clade-wide character displacement patterns in some adaptive radiations, including Darwin’s finches; however, these patterns are not prevalent across animal clades as a whole. Three types of diversification model are also compared here, including the novel interaction-based diversification model. This new model links trait space densities to diversification rates, suppressing diversification among closely packed species. Although these models have a similar conceptual basis, in terms of the accumulation of filled niches, they produce quite different evolutionary histories. The implications of ecological interactions between species are discussed, both for data interpretation and for future modelling approaches.
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Hoehn, Kenneth. "Evolutionary models of antibody lineages." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:ae1fcd96-d858-4f6d-8d99-46b678b2625d.
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Antibodies are proteins released into the blood and mucosa to identify and neutralize invading pathogens by binding to structures on their surface (antigens). Before being exported as antibodies, these vital components of the adaptive immune system are expressed, and refined, as membrane-bound B cell receptors (BCRs). BCRs are initially formed through somatic recombination of germline DNA, creating a large repertoire of unique sequences. After encountering antigen for the first time, BCRs undergo an evolutionary process of somatic mutation and clonal selection leading to improved antigen binding. Recently, next-generation sequencing has provided an unprecedented ability to characterize the genetic diversity of BCRs within individuals. Chapter 1 of this thesis overviews the work done elsewhere in the field until now. Chapter 2 uses summary statistics applied to high-throughput sequence data from a clinical trial to explore the genetic changes that occur in the repertoire during HIV infection. The results of these analyses motivated a more rigorous, model-based approach to understanding BCR diversity. Chapter 3 introduces a new phylogenetic substitution model that relaxes common model assumptions that are violated by somatic hypermutation. Chapter 4 expands this model to incorporate previously defined empirical models of somatic hypermutation, providing a more complete model of B cell maturation. Chapter 5 uses the models developed in Chapters 4 and 5 to explore dynamics of clonal selection during the maturation of three HIV broadly neutralizing antibody lineages. Finally, Chapter 6 shows how this framework may be scaled up to characterize data from entire BCR repertoires from a phylogenetic perspective.
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梁慧敏 and Wai-man Wanthy Leung. "Evolutionary optimisation of industrial systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B30252994.
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Quickfall, Christopher G. "Models of the major evolutionary transitions." Thesis, University of Sheffield, 2016. http://etheses.whiterose.ac.uk/14383/.
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This thesis is concerned with the major transitions view of evolution; the idea that general principles operate in the evolution of each new level of the biological hierarchy (Bourke, 2011). We discuss the theoretical background of this field, focussing on inclusive fitness theory and multi-level selection theory, different approaches to analysing the selection of traits. Many of the commonalities between different transitions are dependent on whether they occur within or between species, and whether relatedness is absent (`egalitarian') or present (`fraternal') (Queller, 1997). Altruism underpins fraternal transitions, and mutually beneficial behaviour underpins egalitarian transitions (Bourke, 2011). We focus on several different models relating to this four-way decomposition. Firstly, we focus on arguments that between-species donation may amount to between-species altruism; this has been a point of contention within the literature (Fletcher and Doebeli, 2009; Gardner et al., 2011; Wyatt et al., 2013). We discuss both deterministic (resting on an assumption of quasi-linkage equilibrium) and stochastic approaches to a simple model of between-species donation, finding that stable donation behaviour can evolve in the presence of assortment across all loci, but is vulnerable to unassorted modifiers. We argue that this behaviour can be interpreted as within-species altruism, using the other species as a vector for altruism, and, further, consider our models in relation to the current literature on greenbeards. Our second model concerns maternally-transmitted sex-distorting endosymbionts. Many species, particularly insect populations, are infected by sex-distorting parasites such as the bacteria Wolbachia, which are maternally-transmitted; thus, distortion of sex ratios towards the production of females may be beneficial to the symbiont. We investigate the potential for a reproductive parasite to transition towards mutualism, laying the foundation for an egalitarian transition between species; in particular, we find that population structure is key to this transition. Finally, we discuss several potential avenues for future research; in particular, we note that the social group transformation phase of a major transition involves a number of open questions, or ideas open to further investigation.
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McKenzie, Andy. "Stochastic speciation models for evolutionary trees." Thesis, University of Canterbury. Mathematics and Statistics, 2000. http://hdl.handle.net/10092/5597.
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Phylogenetic trees are widely used in biology to represent evolutionary relationships between species. As the details of the evolutionary process are mostly unknown, modelling work on the shapes of these trees has had to incorporate a random component. Two null models introduced for this purpose are the uniform model and the Yule model. A third model, the comb model, is useful for giving bounds on theoretical results. We investigate some mathematical properties of these three models.
Let the distance between two nodes be the number of edges separating them. We find exact formulae for the mean distance of a randomly chosen leaf from the root, and for the mean distance between two randomly chosen leaves of a rooted tree. In addition, for the Yule model we find the probability distribution for the distance of randomly chosen leaf from the root.
A cherry is a pair of leaves which are adjacent to a common node. By realising the process of cherry formation by extended Polya urn models we show that the number of cherries is asymptotically normal. This allows us to develop simple statistical tests for the Yule and uniform null hypotheses for the growth of rooted trees. A triplet is a cherry and a pendant edge that are adjacent to a common node. We also show that the asymptotic distribution of triplets is normal for the Yule model, and put forward a conjecture for the distribution under the uniform model.
The construction of an evolutionary tree is generally a two stage process: an unrooted tree is constructed, then it is rooted. We investigate a method for rooting a tree based on the shape of the tree and the Yule model for the growth of rooted trees. We show that even for trees with large number of leaves the approximate location of the root can be located with high probability.
Let S be a set of two rooted binary trees for which the leaf sets L1, L2 form a partition of the set {l, 2, ... ,n}. We derive a recursion for the number of trees on n leaves that are compatible with the set S. We extend this recursion for a set S of three trees, but show that the numbers of terms required in the recursion grows at least exponentially with the number of trees in the set S.
Let S be a set of rooted binary trees. A tree which is a sub-tree of each of the trees in the set is called an agreement sub-tree, and such a tree with the maximum number of possible leaves is called a maximum agreement sub-tree (MAST). We derive an upper bound for the probability that two randomly generated trees have a MAST with number of leaves greater than or equal to a given value s. We find the form the upper bound takes when the trees are generated according to the uniform and Yule models.
The entropy of a probability distribution is equal to the mean information, where the information of an event E is - log P (E). We derive exact and asymptotic formulae for the entropy of the comb, uniform and Yule probability distributions. We show that the comb, uniform, and Yule models satisfy a property called group elimination. A special case of the property of group elimination is sampling consistency.
We show that for any probability distribution on trees that satisfies sampling consistency there is an upper bound on the probability of the fully symmetric tree shapes.
We introduce a modification of the Yule model in which the speciation rate is a function of the time since the last speciation event of a lineage. Using analytical methods we investigate the probability (conditional and unconditional) of the symmetric tree on four leaves under this modified model. If the speciation rate is constant then the probability of the symmetric tree is the same as in the Yule model. Making the speciation rate zero for a period after a speciation event, then constant afterwards, is found to make the symmetric tree more probable. If the speciation rate is constant for some period after a speciation event, then subsequently zero, the symmetric tree is found to be less probable.
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Poulsen, Anders Udo. "Essays on evolutionary models of bargaining." Thesis, University of Essex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343583.
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TITO, EDISON AMERICO HUARSAYA. "EVOLUTIONARY INFERENCE APPROACHES FOR ADAPTIVE MODELS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2003. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=3726@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOEm muitas aplicações reais de processamento de sinais, as observações do fenômeno em estudo chegam seqüencialmente no tempo. Consequentemente, a tarefa de análise destes dados envolve estimar quantidades desconhecidas em cada observação concebida do fenômeno. Na maioria destas aplicações, entretanto, algum conhecimento prévio sobre o fenômeno a ser modelado está disponível. Este conhecimento prévio permite formular modelos Bayesianos, isto é, uma distribuição a priori sobre as quantidades desconhecidas e uma função de verossimilhança relacionando estas quantidades com as observações do fenômeno. Dentro desta configuração, a inferência Bayesiana das quantidades desconhecidas é baseada na distribuição a posteriori, que é obtida através do teorema de Bayes. Infelizmente, nem sempre é possível obter uma solução analítica exata para esta distribuição a posteriori. Graças ao advento de um formidável poder computacional a baixo custo, em conjunto com os recentes desenvolvimentos na área de simulações estocásticas, este problema tem sido superado, uma vez que esta distribuição a posteriori pode ser aproximada numericamente através de uma distribuição discreta, formada por um conjunto de amostras. Neste contexto, este trabalho aborda o campo de simulações estocásticas sob a ótica da genética Mendeliana e do princípio evolucionário da sobrevivência dos mais aptos. Neste enfoque, o conjunto de amostras que aproxima a distribuição a posteriori pode ser visto como uma população de indivíduos que tentam sobreviver num ambiente Darwiniano, sendo o indivíduo mais forte, aquele que possui maior probabilidade. Com base nesta analogia, introduziu-se na área de simulações estocásticas (a) novas definições de núcleos de transição inspirados nos operadores genéticos de cruzamento e mutação e (b) novas definições para a probabilidade de aceitação, inspirados no esquema de seleção, presente nos Algoritmos Genéticos. Como contribuição deste trabalho está o estabelecimento de uma equivalência entre o teorema de Bayes e o princípio evolucionário, permitindo, assim, o desenvolvimento de um novo mecanismo de busca da solução ótima das quantidades desconhecidas, denominado de inferência evolucionária. Destacamse também: (a) o desenvolvimento do Filtro de Partículas Genéticas, que é um algoritmo de aprendizado online e (b) o Filtro Evolutivo, que é um algoritmo de aprendizado batch. Além disso, mostra-se que o Filtro Evolutivo, é em essência um Algoritmo Genético pois, além da sua capacidade de convergência a distribuições de probabilidade, o Filtro Evolutivo converge também a sua moda global. Em conseqüência, a fundamentação teórica do Filtro Evolutivo demonstra, analiticamente, a convergência dos Algoritmos Genéticos em espaços contínuos. Com base na análise teórica de convergência dos algoritmos de aprendizado baseados na inferência evolucionária e nos resultados dos experimentos numéricos, comprova-se que esta abordagem se aplica a problemas reais de processamento de sinais, uma vez que permite analisar sinais complexos caracterizados por comportamentos não-lineares, não- gaussianos e nãoestacionários.
In many real-world signal processing applications, the phenomenon s observations arrive sequentially in time; consequently, the signal data analysis task involves estimating unknown quantities for each phenomenon observation. However, in most of these applications, prior knowledge about the phenomenon being modeled is available. This prior knowledge allows us to formulate a Bayesian model, which is a prior distribution for the unknown quantities and the likelihood functions relating these quantities to the observations. Within these settings, the Bayesian inference on the unknown quantities is based on the posterior distributions obtained from the Bayes theorem. Unfortunately, it is not always possible to obtain a closed-form analytical solution for this posterior distribution. By the advent of a cheap and formidable computational power, in conjunction with some recent developments in stochastic simulations, this problem has been overcome, since this posterior distribution can be obtained by numerical approximation. Within this context, this work studies the stochastic simulation field from the Mendelian genetic view, as well as the evolutionary principle of the survival of the fittest perspective. In this approach, the set of samples that approximate the posteriori distribution can be seen as a population of individuals which are trying to survival in a Darwinian environment, where the strongest individual is the one with the highest probability. Based in this analogy, we introduce into the stochastic simulation field: (a) new definitions for the transition kernel, inspired in the genetic operators of crossover and mutation and (b) new definitions for the acceptation probability, inspired in the selection scheme used in the Genetic Algorithms. The contribution of this work is the establishment of a relation between the Bayes theorem and the evolutionary principle, allowing the development of a new optimal solution search engine for the unknown quantities, called evolutionary inference. Other contributions: (a) the development of the Genetic Particle Filter, which is an evolutionary online learning algorithm and (b) the Evolution Filter, which is an evolutionary batch learning algorithm. Moreover, we show that the Evolution Filter is a Genetic algorithm, since, besides its capacity of convergence to probability distributions, it also converges to its global modal distribution. As a consequence, the theoretical foundation of the Evolution Filter demonstrates the convergence of Genetic Algorithms in continuous search space. Through the theoretical convergence analysis of the learning algorithms based on the evolutionary inference, as well as the numerical experiments results, we verify that this approach can be applied to real problems of signal processing, since it allows us to analyze complex signals characterized by non-linear, nongaussian and non-stationary behaviors.
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Williams, Bryn V. "Evolutionary neural networks : models and applications." Thesis, Aston University, 1995. http://publications.aston.ac.uk/10635/.
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The scaling problems which afflict attempts to optimise neural networks (NNs) with genetic algorithms (GAs) are disclosed. A novel GA-NN hybrid is introduced, based on the bumptree, a little-used connectionist model. As well as being computationally efficient, the bumptree is shown to be more amenable to genetic coding lthan other NN models. A hierarchical genetic coding scheme is developed for the bumptree and shown to have low redundancy, as well as being complete and closed with respect to the search space. When applied to optimising bumptree architectures for classification problems the GA discovers bumptrees which significantly out-perform those constructed using a standard algorithm. The fields of artificial life, control and robotics are identified as likely application areas for the evolutionary optimisation of NNs. An artificial life case-study is presented and discussed. Experiments are reported which show that the GA-bumptree is able to learn simulated pole balancing and car parking tasks using only limited environmental feedback. A simple modification of the fitness function allows the GA-bumptree to learn mappings which are multi-modal, such as robot arm inverse kinematics. The dynamics of the 'geographic speciation' selection model used by the GA-bumptree are investigated empirically and the convergence profile is introduced as an analytical tool. The relationships between the rate of genetic convergence and the phenomena of speciation, genetic drift and punctuated equilibrium arc discussed. The importance of genetic linkage to GA design is discussed and two new recombination operators arc introduced. The first, linkage mapped crossover (LMX) is shown to be a generalisation of existing crossover operators. LMX provides a new framework for incorporating prior knowledge into GAs. Its adaptive form, ALMX, is shown to be able to infer linkage relationships automatically during genetic search.
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vanCort, Tracy. "Computational Evolutionary Linguistics." Scholarship @ Claremont, 2001. https://scholarship.claremont.edu/hmc_theses/137.
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Languages and species both evolve by a process of repeated divergences, which can be described with the branching of a phylogenetic tree or phylogeny. Taking advantage of this fact, it is possible to study language change using computational tree building techniques developed for evolutionary biology. Mathematical approaches to the construction of phylogenies fall into two major categories: character based and distance based methods. Character based methods were used in prior work in the application of phylogenetic methods to the Indo-European family of languages by researchers at the University of Pennsylvania. Discussion of the limitations of character-based models leads to a similar presentation of distance based models. We present an adaptation of these methods to linguistic data, and the phylogenies generated by applying these methods to several modern Germanic languages and Spanish. We conclude that distance based for phylogenies are useful for historical linguistic reconstruction, and that it would be useful to extend existing tree drawing methods to better model the evolutionary effects of language contact.
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Parks, Sarah Louise. "Mathematical models and statistics for evolutionary inference." Thesis, University of Cambridge, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708749.
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Li, Xinyang. "Evolutionary mechanism design using agent-based models." Thesis, University of Bath, 2012. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558876.
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This research complements and combines market microstructure theory and mechanism design to optimize the market structure of financial markets systematically. We develop an agent-based model featuring near-zero-intelligence traders operating in a call market with a wide range of trading rules governing the determination of prices, which orders are executed as well as a range of parameters regarding market intervention by market makers and the presence of informed traders. The market structure which generates the best market performance is determined by applying the search technique Population-based Incremental Learning, guided by a number of performance measures, including maximizing trading volume or price, minimizing bid-ask spread or return volatility. We investigate the credibility of our model by observing the trading behavior of near-zero-intelligence traders with stylized facts in real markets. Based on computer simulations, we conform that the model is capable to reproduce some of the most important stylized facts found in financial markets. Thereafter, we investigate the best found market structure using both single-objective optimization and multi-objective optimization techniques. Our results suggest that the best-found combination of trading rules used to enhance trading volume may not be applied to achieve other objectives, such as reducing bid-ask spread. The results of single-objective optimization experiments show that significantly large tick sizes appear in the best market structures in most cases, except for the case of maximizing trading volume. The tick size is always correlated with the selection of multi-price rules. Though there is no particular combination of priority rule and multiprice rule achieving the best market performance, the time priority rule and the closest multi-price rule are the most frequently obtained rules. The level of market transparency and the extend of market maker intervention show ambiguous results as their representative parameter values change in a wide range. We also nd that the results of multi-objective optimization experiments are much similar to those obtained in the single-objective optimization experiments, except for the market transparency represented by the fraction of informed trader, which shows a clear trend in the multi-objective optimization. Using the results obtained from this research we can derive recommendations for exchanges and regulators on establishing the optimal market structure; for securities issuers on choosing the best exchange for their listing; and for investors on choosing the most suitable exchange for trading.
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Schwämmle, Veit. "Simulations on evolutionary phenomena with ageing models." [S.l. : s.n.], 2006. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-27556.
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Gallagher, E. M. "Evolutionary models for the origins of agriculture." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/10028979/.
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The transition from hunting and gathering to farming at the end of the Pleistocene was one of the most important events in human history, having major impacts on human demography, evolution, health, culture, technology, and social stratification. The reasons why some societies switched to farming are still debated, with climate stabilisation and population pressure as popular hypotheses. However, since these processes occurred so long ago, investigating the transition can be difficult without the use of mathematical models. In this thesis I investigate the effect of various factors, including population size, conservatism, property rights, environmental conditions, climate variability, and mobility, on the transition to farming using evolutionary models. I do this by implementing an intensive parameter sensitivity analysis method on an existing game theoretical model (Bowles and Choi, 2013) for the origins of agriculture, and also develop and explore my own agent-based models of social and environmental interactions. Using the Bowles and Choi model, I find that the key parameters for the emergence of farming are group structuring, group size, conservatism, and farming-friendly property rights. The analysis of this model also shows that although advantageous, it is not essential for the emergence of farming for farming productivity to be greater than foraging productivity. In the development of my own model, I first consider mobility changes in a forager population, and find that low depletion and high growth rates can lead to reduced mobility, low fitness, and high population density. When I add subsistence behaviours to the model I find that three behaviours can evolve in response to different environmental conditions; mobile foraging, sedentary foraging, and sedentary farming. I also find a relationship between reduced mobility, the emergence of farming, decreased fitness and high population densities. Additionally, my model predicts that population pressure was caused by, but not causal of, the switch to farming. Importantly, these results concur with the observed archaeological data and ethnographic record, and highlight the value of using modelling to validate and/or challenge observed data.
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Mendes, Luiz Themystokliz Sanctos. "Evolutionary models of rotating low mass stars." Universidade Federal de Minas Gerais, 1999. http://hdl.handle.net/1843/BUOS-9GGP5S.
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We have investigated the combined effects of rotation and internal ngular momentum redistribution on the structure and evolution of low mass tars, from the pre-main sequence to the main sequence phase. As a tool for that study, the ATON stellar evolutionary code (Mazzitelli 1989; Ventura et al. 1998) has been modified in order to include those effects. Rotation as implemented according to the equipotential technique developed by Kippenhahn and Thomas (1970) and later improved by Endal and Sofia (1976). Angular momentum redistribution in radiative regions was modeled through an advection-diffusion partial differential equation based on the framework originally introduced by Chaboyer and Zahn (1992), which is based on the sole assumption of stronger turbulent transport in the horizontal direction than in the vertical one. The diffusion coefficient of this equation is obtained from characteristic lengths and velocities of typical rotation-induced hydrodynamical instabilities. This improved code was used to compute a series of rotating low mass stellar models (with masses ranging from 1.2 Msun down to 0.6 Msun). Regarding the structural (hydrostatic) effects of rotation, the general features of these models show that rotating stars behave as if they were non-rotating stars of slightly lower masses, in accordance with previous results by other researchers. A study of this mass-lowering effect for the considered range of masses shows that rotation decreases lithium depletion while the star is fully convective but increases it as soon as the star develops a radiative core. The net effect is a enhanced lithiumepletion, in disagreement with observational data which suggest that faster rotators in young open clusters experience less lithium depletion. Angular momentum redistribution in the considered models is very effective in smoothing their internal angular velocity profile as soon as the star reaches the zero age main sequence, but fails to reproduce the flat solar rotation rate obtained from helioseismology, indicating that, in the Sun, angular momentum transport is more efficient than current models. The internal angular momentum transport also contributes to a still higher lithium depletion than the models computed with only the structural effects of rotation, thus suggesting that other physical phenomena must play a role regarding both lithium depletion and the rotation profile evolution of these stars.Neste trabalho nós investigamos os efeitos combinados da rotação e da redistribuição de momento angular em estrelas de baixa massa, desde a etapa pré-sequência principal até a sequência principal. Como uma ferramenta para tal estudo, o código evolutivo estelar ATON (Mazzitelli 1989; Ventura et al. 1998b) foi alterado de forma a incluir tais efeitos. A rotação foi implementada segundo a técnica de superfícies equipotenciais desenvolvida por Kippenhahn & Thomas (1970) e posteriormente aperfeiçoada por Endal & Sofia (1976). A redistribuição de momento angular foi modelada por intermédio de uma equação diferencial parcial do tipo difusivo-advectivo, com base na teoria originalmente desenvolvida por Chaboyer & Zahn (1992), a qual considera como único pressuposto que o transporte turbulento é muito mais forte na direção horizontal que na vertical. O coeficiente de difusão desta equação é obtido a partir de comprimentos e velocidades característicos de instabilidades hidrodinâmicas induzidas pela rotação. Este novo código foi empregado para calcular uma série de modelos com rotação de estrelas de baixa massa (na faixa de 0.6 M_ a 1.2 M_). As características gerais destes modelos, com relação aos efeitos estruturais (hidrostáticos) da rotação, mostram que estrelas com rotação comportam-se como se fossem estrelas sem rotação, porém de massa ligeiramente menor, estando de acordo com resultados anteriores por outros pesquisadores. Um estudo deste efeito de abaixamento de massa" para a faixa de massas considerada revela que a rotação diminui a queima de lítio enquanto a estrela é totalmente convectiva, mas aumenta a mesma tão logo a estrela desenvolve um núcleo radiativo. O efeito líquido é um aumento da queima de lítio, em desacordo com dados observacionais que mostram que as estrelas de aglomerados abertos jovens que giram mais rápido são as que apresentam menor queima de lítio. A redistribuição de momento angular nos modelos considerados torna-se muito eficaz na suavização do gradiente interno de velocidade angular tão logo a estrela atinja a idade zero na sequência principal, mas não é capaz de reproduzir a curva de rotação solar obtida da heliosismologia, indicando que o transporte de momento angular no Sol é mais eficiente do que o predito pelos atuais modelos. O transporte interno de momento angular também contribui para uma queima ainda maior de lítio com relação aos modelos calculados somente com os efeitos estruturais. Isto sugere que outros fenômenos físicos devem ser importantes tanto para a queima de lítio quanto para a evolução da curva de velocidade angular das estrelas.
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Sharabati, Walid. "Multi-mode and evolutionary networks." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3384.
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Thesis (Ph.D.)--George Mason University, 2008.Vita: p. 214-215. Thesis director: Edward J. Wegman, Yasmin H. Said Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computational Sciences and Informatics. Title from PDF t.p. (viewed Mar. 9, 2009). Includes bibliographical references (p. 209-213). Also issued in print.
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Dukkipati, Ambedkar. "ACE-Model: A Conceptual Evolutionary Model For Evolutionary Computation And Artificial Life." Thesis, Indian Institute of Science, 2002. http://hdl.handle.net/2005/47.
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Darwinian Evolutionary system - a system satisfying the abstract conditions: reproduction with heritable variation, in a finite world, giving rise to Natural Selection encompasses a complex and subtle system of interrelated theories, whose substantive transplantation to any artificial medium let it be mathematical model or computational model - will be very far from easy. There are two motives in bringing Darwinian evolution into computational frameworks: one to understand the Darwinian evolution, and the other is to view Darwinian evolution - that carries out controlled adaptive-stochastic search in the space of all possible DNA-sequences for emergence and improvement of the living beings on our planet - as an optimization process, which can be simulated in appropriate frameworks to solve some intractable problems. The first motive led to emerging field of study commonly referred to as Artificial Life, and other gave way to emergence of Evolutionary Computation, which is speculated to be the only practical path to the development of ontogenetic machine intelligence. In this thesis we touch upon all the above aspects.
Natural selection is the central concept of Darwinian evolution and hence capturing natural selection in computational frameworks which maintains the spirit of Darwinian evolution in the sense of conventional, terrestrial and biological perspectives is essential. Naive models of evolution define natural selection as a process which brings in differential reproductive capabilities in organisms of a population, and hence, most of the evolutionary simulations in Artificial Life and Evolutionary Computation implement selection by differential reproduction: the Attest members of the population are reproduced preferentially at the expense of the less fit members of the population. Formal models in evolutionary biology often subdivide selection into components called 'episodes of selection' to capture the different complex mechanisms of nature by which Darwinian evolution can occur. In this thesis we introduce the concept of 'episodes of selection' into computational frameworks of Darwinian evolution by means of A Conceptual Evolutionary model (ACE-model). ACE-model is proposed to be simple and yet it captures the essential features of modern evolutionary perspectives in evolutionary computation framework.
ACE-model is rich enough to offer abstract and structural framework for evolutionary computation and can serve as a basic model for evolutionary algorithms. It captures selection in two episodes in two phases of evolutionary cycle and it offers various parameters by which evolutionary algorithms can control selection mechanisms. In this thesis we propose two evolutionary algorithms namely Malthus evolutionary algorithms and Malthus Spencer evolutionary algorithms based on the ACE-model and we discuss the relevance of parameters offered by ACE-model by simulation studies.
As an application of ACE-model to artificial life we study misconceptions involved in defining fitness in evolutionary biology, and we also discuss the importance of introducing fitness landscape in the theories of Darwinian evolution.
Another important and independent contribution of this thesis is: A Mathematical Abstraction of Evolutionary process. Evolutionary process is characterized by Evolutionary Criteria and Evolutionary Mechanism which are formalized by classical mathematical tools. Even though the model is in its premature stage to develop any theory based on it, we develop convergence criteria of evolutionary process based on this model.
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Skolicki, Zbigniew Maciej. "An analysis of island models in evolutionary computation." Fairfax, VA : George Mason University, 2007. http://hdl.handle.net/1920/2954.
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Thesis (Ph. D.)--George Mason University, 2007.Title from PDF t.p. (viewed Jan. 22, 2008). Thesis director: Kenneth A. De Jong. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science. Vita: p. 422. Includes bibliographical references (p. 413-421). Also available in print.
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Bloomquist, Erik William. "Bayesian hierarchical models to untangle complex evolutionary histories." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1971755201&sid=35&Fmt=2&clientId=1564&RQT=309&VName=PQD.
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Komuro, Rie. "Multi-objective evolutionary algorithms for ecological process models /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/6786.
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Gamalielsson, Jonas. "Models for Protein Structure Prediction by Evolutionary Algorithms." Thesis, University of Skövde, Department of Computer Science, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-623.
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Evolutionary algorithms (EAs) have been shown to be competent at solving complex, multimodal optimisation problems in applications where the search space is large and badly understood. EAs are therefore among the most promising classes of algorithms for solving the Protein Structure Prediction Problem (PSPP). The PSPP is how to derive the 3D-structure of a protein given only its sequence of amino acids. This dissertation defines, evaluates and shows limitations of simplified models for solving the PSPP. These simplified models are off-lattice extensions to the lattice HP model which has been proposed and is claimed to possess some of the properties of real protein folding such as the formation of a hydrophobic core. Lattice models usually model a protein at the amino acid level of detail, use simple energy calculations and are used mainly for search algorithm development. Off-lattice models usually model the protein at the atomic level of detail, use more complex energy calculations and may be used for comparison with real proteins. The idea is to combine the fast energy calculations of lattice models with the increased spatial possibilities of an off-lattice environment allowing for comparison with real protein structures. A hypothesis is presented which claims that a simplified off-lattice model which considers other amino acid properties apart from hydrophobicity will yield simulated structures with lower Root Mean Square Deviation (RMSD) to the native fold than a model only considering hydrophobicity. The hypothesis holds for four of five tested short proteins with a maximum of 46 residues. Best average RMSD for any model tested is above 6Å, i.e. too high for useful structure prediction and excludes significant resemblance between native and simulated structure. Hence, the tested models do not contain the necessary biological information to capture the complex interactions of real protein folding. It is also shown that the EA itself is competent and can produce near-native structures if given a suitable evaluation function. Hence, EAs are useful for eventually solving the PSPP.
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Donati, Beatrice. "Graph models and algorithms in (co-)evolutionary contexts." Thesis, Lyon 1, 2014. http://www.theses.fr/2014LYO10235/document.
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Cette thèse s'inscrit dans le cadre de la bioinformatique. Les outils mathématiques les plus utilisés dans ce travail relèvent de la théorie des graphes, des statistiques, de la théorie des ensembles et des mathématiques discrètes. Ces mathématiques ont permis de développer des modèles de systèmes biologiques ainsi que des algorithmes efficaces dans l'étude concrète de ces modèles. La nécessité d'analyses de jeux de données de très grande taille a rendu critique dans notre démarche cette notion d'efficacité des algorithmes. Il faut enfin remarquer que le champ biologique qui a servi de support à cette thèse nous a conduit à explorer un domaine particulier au sein de la théorie de la complexité, à savoir le développement et l'analyse des algorithmes d'énumération [etc...]In the results presented in the present manuscripts, graph theory and combinatorial optimizationtecniques, have been used to model and solve biological problems. The manuscript is divided in twoparts, each one containing the mathematical and biological background of a given application and ouroriginal contributions to it.Part I groups a set of results designed for phylogenetics analysis, and in particular for reconstructingthe co-evolution of two groups of organisms (the so called co-phylogeny reconstruction problem).Although the addressed problem was treated in the available there was no method that solved suchproblem in a complete and efficient way. We thus developed and implemented a new one, calledEucalypt, with this purpose in mind. This not only provides a novel and usable software for cophylogenyreconstruction but also allows to investigate how the event-based model performs inpractice in terms of thenumber and quality of the solutions obtained. We compared our method to the available software. Bylooking at the results obtained, some interesting considerations about the advantages anddisadvantages of the commonly accepted mathematical model could be drawn. Finally, we introduceda new version of the problem where the host-switches are distance bounded: the k-bounded-All-MPRproblem. Eucalypt solves both problems in polynomial delay. These results have been accepted forpublication by the jounal Algorithms for Molecular Biology. The relative software is publicyavailable.Our studies show that the 'most parsimonious scenario' approach presents some limitationsthat cannot be ignored. To deal with these problems, we developed a second algorithm, called Coala,based on an approximate Bayesian computation approach for estimating the frequency of the events.The benefits of this method are twofold: it provides more confidence in the set of costs to be used in areconciliation, and it allows to estimate the frequency of the events in the cases where a reconciliationmethod cannot be applied. These results are currently under review by the jounal Systematic Biology.The relative software is publicy available.In Part 2 another set of studies is presented. Our original model for the contig scaffolding problem,and our algorithm MeDuSa, are presented and tested. Unlike traditional software, it does not rely eitheron paired-end information of sequencing reads or on a phylogenetic distance of the microorganismsused in the analysis. This drastically increases the usability of our software and, at the same time,reduces the computational time required for genome scaffolding. We show that the algorithmimplemented in MeDuSa, in most cases, is capable of producing less and longer scaffolds incomparison to commonly used scaffolders, while maintaining high accuracy and correctness of thepredicted joins. These results are currently under revision by the journal Bioinformatics.Finally, during the development of this method we encountered some pure theoretical open problemsand we decided to dedicate part of our job to their analysis. The last chapter is then dedicated to a setof problems, all related to the Implicit Hitting set enumeration problem. After some formal definitions,an original NP-completeness result is presented and the future directions of our work are described
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Almeida, Costa Da Cruz José António. "Development of evolutionary models for non-coding RNAs." Strasbourg, 2011. http://www.theses.fr/2011STRA6099.
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[. . . ]Pour répondre à la nécessité d'un pipeline d'annotation d'ARNnc rapide et fiable dans le contexte des projets de séquençage génomique de grand envergure, tels que lesprojets Génolevures et Dikaryome, nous avons mis au point deux pipelines d'annotation automatique, intégrant des outils disponibles publiquement, de recherche d'ARNnc par homologie et de novo. Les deux pipelines ont été appliqués à 15 génomes de levures et ont permis de trouver et d'annoter 1051 gènes d'ARNnc, correspondant à plus de 80% des ARNnc attendus pour ces génomes – si on prend comme référence le nombre d'ARNnc chez S. Cerevisiae. En outre, plusieurs nouveaux ARNnc, encore inconnus chez les Saccharomycotinae, ont été détectés. De plus, nous avons mis en évidence un ensemble de nouvelles observations sur la synténie de gènes d'ARNnc et de nouveaux exemples de domaines supplémentaires dans certains ARNnc essentiels. Les résultats montrent la faisabilité de la recherche automatique des ARNnc dans les génomes complets et l'utilité de telles approches dans les grands projets de séquençage et d'annotation génomique. L'intégration complète, dans le pipeline de développement, de nouveaux outils tels que ceux de prédiction de gènes d'ARNnc de novo ainsi que la possibilité de traiter des données provenant d'autres sources, comme les expériences de séquençage profond, sont les prochains défis à court terme dans cette ligne de travail. La confirmation expérimentale de ces observations, qui est au-delà de l'approche bioinformatique, doit être le prolongement naturel du projet d'annotation. Dans le strict domaine bioinformatique, le développement de nouvelles approches pour détecter les gènes d'ARNnc insaisissables tels que la composante ARN de la télomerase seraient des ajouts utiles à notre pipeline. Enfin, j'ai développé un algorithme original pour détecter les modules structuraux d'ARN uniquement à partir des informations de séquence (RMDetect). L'algorithme a été conçu pour identifier les modules structuraux connus dans les séquences simples et dans les alignements multiples en l'absence de toute autre information. L'algorithme utilise un réseau bayésien pour la représentation des modules couplé à l'estimation de la probabilité conjointe des paires de bases Watson-Crick participant à des modules. Actuellement, quatre modules peuvent être recherchés : la boucle "G-bulge'', le"Kink Turn'', la boucle C et la boucle "tandem GA''. Dans des séquences de test de contrôle, nous avons trouvé l'ensemble des modules connus avec un taux de fausse découverte de 0. 23. En cherchant les 1444 alignements publiquement disponibles, nous avons identifié 21 modules encore non détectés et 141 modules connus. RMDetect est une étape utile pour combler le fossé entre l'analyse pure de séquences et l'étude structurale de l'ARN. De plus, il peut être utilisé dans l'affinement des structures 2D d'ARN, dans l'assemblage de modèles 3D, et dans la recherche et l'annotation de gènes d'ARN structurés dans les génomes. Nous espérons améliorer l'approche actuelle par l'ajout de nouveaux modèles structuraux. La recherche de modules structuraux dans des génomes complets serait la prochaine étape dans cette ligne de recherche[. . . ]To answer the need for a fast and reliable ncRNA annotation in the context of large scale genome sequencing projects (Génolevures and Dikaryome projects), I implemented two automatic annotation pipelines, integrating publicly available tools, for homology and \emph{de novo} ncRNA search in genomes. Both pipelines were applied to 15 yeast genomes and 1051 ncRNA genes were found, corresponding to more than 80% of the expected ncRNAs (assuming the number of ncRNAs from S. Cerevisiae as reference). Additionally I identified : (i) several new potential ncRNAs; (ii) several new synteny relationships between ncRNA loci; and (iii) new examples of extended structural domains in well known essential ncRNAs. These results show the feasibility of automatic search for ncRNAs in full genomes and the utility of such approaches in large genome annotation projects. Finally, I developed a new algorithm to detect structural RNA modules in sequences : RMDetect. It was designed to identify 3D structural modules in RNA sequences. It uses a Bayesian Network to represent the searched modules and the joint base pair probability estimation to select candidates. Four modules can be searched for: G-bulges, Kink-turns, C-loop and Tandem-GAs. In test sequences all of the known modules were found with a false discovery rate of 0. 23. In 1444 publicly available alignments 21 yet unreported and 141 known modules were identified. RMDetect is a step to bridge the gap between sequence analysis and 3D RNA studies. It can be used in the refinement of RNA 2D structures, the assembly of RNA 3D models, and the search of structured ncRNAs in genomic data
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Li, Li, and 李麗. "Evolutionary optimization methods for mass customizing platform products." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B3955790X.
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Ghachem, Montasser. "Essays in Evolutionary Game Theory." Doctoral thesis, Stockholms universitet, Nationalekonomiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-132433.
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Evolutionary game theory tries to explain the emergence of stable behaviors observed in human and animal societies. Prominent examples of such behaviors are cooperative and conformist behaviors. In the first part of the thesis, we develop a model of indirect reciprocity with institutional screening to study how institutions may promote cooperative behavior. We show that cooperation can emerge if screening institutions are sufficiently reliable at identifying cooperators. The second part presents a large-population learning model in which individuals update their beliefs through time. In the model, only one individual updates his beliefs each period. We show that a population, playing a game with two strategies, eventually learns to play a Nash equilibrium. We focus on coordination games and prove that a unique behavior arises both when players use myopic and perturbed best replies. The third part studies the payoff calculation in an evolutionary setting. By introducing mutual consent as a requirement for game play, we provide a more realistic alternative way to compute payoffs.At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 3: Manuscript.
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Thompson, Denis. "Finding homologous genes with primers designed using evolutionary models." NCSU, 2003. http://www.lib.ncsu.edu/theses/available/etd-10232003-122816/.
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Genes homologous to a set of known, aligned, genes can be found by screening DNA libraries with PCR. PCR primers for such screens are commonly designed via a method described by Sells and Chernoff (1995). This standard design method does not make use of information about the evolutionary relationship between the known genes. The present study investigated the efficacy of using information about evolutionary relationships (inferred from the sequence data) in the design of PCR primers. This study compares the standard primer design method (represented herein by a modified multinomial distribution) with evolutionary model based primer design methods. The primer design method that, given an alignment of known sequences with one sequence left out, assigned a higher probability, on average, to the left-out sequence, was defined as the better method. By this measure of relative performance, an evolutionary model based primer design method sensitive to states correlated across sites of a sequence, outperformed the standard method, on the alignments studied.
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Cox, Chris. "Inferring and exploiting compact models of evolutionary problem structure." Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/379362/.
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In both natural and artificial evolution, populations search a space of possibilities using the mechanisms of natural selection and random variation. However, not all variations are equally likely. The directions which variation can take are themselves a key part of the evolutionary machinery, determining the ability of evolution to create diversity whilst obeying the constraints of phenotype space. To be effective they must reflect the structure of the selective environment in which they exist. Evolutionary algorithms are often designed with a priori assumptions about this structure, but it can also be learned on the fly using “model-building” algorithms. However, there are many open questions: what information do populations contain about their selective environment? How can it be extracted from a population and represented? And how can it be exploited to facilitate more effective evolutionary search? In this thesis, a novel type of lossless compact model called Schema Grammar is introduced. Schema Grammar overcomes the current limitations of compact models by enabling intrinsically non-sequential data to be compressed. It offers a number of advantages over existing model-building approaches. In particular, the model is able to infer a hierarchy of genetic schemata that is consistent with the compositional structure of the selective environment, and has a strong predictive quality with respect to fitness. By using this structure to facilitate variation at many different levels of scale, instances of well-known test problems are shown to be solvable in low-order polynomial time, matching the performance of state of the art methods. The information-theoretic qualities of Schema Grammar also enable evolutionary information to be quantified in novel ways. Building on recent advances in information and complexity theory, the model is used to quantify mutual information between populations and their selective environment, including environments containing complex epistatic structure. It is also used to predict the fitness of individuals by measuring their information distance to a fit population.
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Gaier, Adam. "Accelerating Evolutionary Design Exploration with Predictive and Generative Models." Electronic Thesis or Diss., Université de Lorraine, 2020. http://www.theses.fr/2020LORR0087.
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L'optimisation joue un rôle essentiel dans la conception industrielle, mais ne se limite pas à la minimisation d'une simple fonction, comme le coût ou la résistance. Ces outils sont également utilisés dans les phases conceptuelles, pour mieux comprendre ce qui est possible. Pour soutenir cette exploration, nous nous concentrons sur les algorithmes de diversité de qualité (QD), qui produisent des ensembles de solutions variées et performantes. Ces techniques nécessitent souvent l'évaluation de millions de solutions, ce qui les rend peu pratiques dans les cas de conception. Dans cette thèse, nous proposons des méthodes pour améliorer radicalement l'efficacité des données de la QD avec l'apprentissage machine, permettant son application à la conception. Dans notre première contribution, nous développons une méthode de modélisation des performances des réseaux neuronaux évolués utilisés pour le contrôle et la conception. Les structures de ces réseaux se développent et changent, ce qui les rend difficiles à modéliser - mais grâce à une nouvelle méthode, nous sommes en mesure d'estimer leurs performances en fonction de leur hérédité, améliorant ainsi l'efficacité des données à plusieurs reprises. Dans notre deuxième contribution, nous combinons l'optimisation basée sur un modèle avec MAP-Elites, un algorithme QD. Un modèle de performance est créé à partir de modèles connus, et MAP-Elites crée un nouvel ensemble de modèles en utilisant cette approximation. Un sous-ensemble de ces conceptions est évalué pour améliorer le modèle, et le processus se répète. Nous montrons que cette approche améliore l'efficacité de MAP-Elites par des ordres de grandeur. Notre troisième contribution intègre des modèles générateurs dans MAP-Elites pour apprendre des codages spécifiques à un domaine. Un auto-codeur variationnel est formé sur les solutions produites par MAP-Elites, capturant la "recette" commune pour une haute performance. Ce codage appris peut ensuite être réutilisé par d'autres algorithmes pour une optimisation rapide, y compris MAP-Elites. Tout au long de cette thèse, bien que notre vision se concentre sur la conception, nous examinons les applications dans d'autres domaines, comme la robotique. Ces avancées ne sont pas exclusives à la conception, mais servent de travail de base à l'intégration de la DQ et de l'apprentissage machineOptimization plays an essential role in industrial design, but is not limited to minimization of a simple function, such as cost or strength. These tools are also used in conceptual phases, to better understand what is possible. To support this exploration we focus on Quality Diversity (QD) algorithms, which produce sets of varied, high performing solutions. These techniques often require the evaluation of millions of solutions -- making them impractical in design cases. In this thesis we propose methods to radically improve the data-efficiency of QD with machine learning, enabling its application to design. In our first contribution, we develop a method of modeling the performance of evolved neural networks used for control and design. The structures of these networks grow and change, making them difficult to model -- but with a new method we are able to estimate their performance based on their heredity, improving data-efficiency by several times. In our second contribution we combine model-based optimization with MAP-Elites, a QD algorithm. A model of performance is created from known designs, and MAP-Elites creates a new set of designs using this approximation. A subset of these designs are the evaluated to improve the model, and the process repeats. We show that this approach improves the efficiency of MAP-Elites by orders of magnitude. Our third contribution integrates generative models into MAP-Elites to learn domain specific encodings. A variational autoencoder is trained on the solutions produced by MAP-Elites, capturing the common “recipe” for high performance. This learned encoding can then be reused by other algorithms for rapid optimization, including MAP-Elites. Throughout this thesis, though the focus of our vision is design, we examine applications in other fields, such as robotics. These advances are not exclusive to design, but serve as foundational work on the integration of QD and machine learning
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Bergerhoff, Leif [Verfasser]. "Evolutionary Models for Signal Enhancement and Approximation / Leif Bergerhoff." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2020. http://d-nb.info/1237268753/34.
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Fryer, Timothy James Osborne. "ESS models of sperm competition." Thesis, University of Sheffield, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266803.
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Mok, Pik-yin, and 莫碧賢. "Evolutionary optimisation of production-control systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B29751020.
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Zechman, Emily Michelle. "Improving Predictability of Simulation Models using Evolutionary Computation-Based Methods for Model Error Correction." NCSU, 2005. http://www.lib.ncsu.edu/theses/available/etd-08082005-105133/.
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Simulation models are important tools for managing water resources systems. An optimization method coupled with a simulation model can be used to identify effective decisions to efficiently manage a system. The value of a model in decision-making is degraded when that model is not able to accurately predict system response for new management decisions. Typically, calibration is used to improve the predictability of models to match more closely the system observations. Calibration is limited as it can only correct parameter error in a model. Models may also contain structural errors that arise from mis-specification of model equations. This research develops and presents a new model error correction procedure (MECP) to improve the predictive capabilities of a simulation model. MECP is able to simultaneously correct parameter error and structural error through the identification of suitable parameter values and a function to correct misspecifications in model equations. An evolutionary computation (EC)-based implementation of MECP builds upon and extends existing evolutionary algorithms to simultaneously conduct numeric and symbolic searches for the parameter values and the function, respectively. Non-uniqueness is an inherent issue in such system identification problems. One approach for addressing non-uniqueness is through the generation of a set of alternative solutions. EC-based techniques to generate alternative solutions for numeric and symbolic search problems are not readily available. New EC-based methods to generate alternatives for numeric and symbolic search problems are developed and investigated in this research. The alternatives generation procedures are then coupled with the model error correction procedure to improve the predictive capability of simulation models and to address the non-uniqueness issue. The methods developed in this research are tested and demonstrated for an array of illustrative applications.
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Chen, Lei. "Construction of Evolutionary Tree Models for Oncogenesis of Endometrial Adenocarcinoma." Thesis, University of Skövde, School of Humanities and Informatics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-25.
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Endometrial adenocarcinoma (EAC) is the fourth leading cause of carcinoma in woman worldwide, but not much is known about genetic factors involved in this complex disease. During the EAC process, it is well known that losses and gains of chromosomal regions do not occur completely at random, but partly through some flow of causality. In this work, we used three different algorithms based on frequency of genomic alterations to construct 27 tree models of oncogenesis. So far, no study about applying pathway models to microsatellite marker data had been reported. Data from genome–wide scans with microsatellite markers were classified into 9 data sets, according to two biological approaches (solid tumor cell and corresponding tissue culture) and three different genetic backgrounds provided by intercrossing the susceptible rat BDII strain and two normal rat strains. Compared to previous study, similar conclusions were drawn from tree models that three main important regions (I, II and III) and two subordinate regions (IV and V) are likely to be involved in EAC development. Further information about these regions such as their likely order and relationships was produced by the tree models. A high consistency in tree models and the relationship among p19, Tp53 and Tp53 inducible
protein genes provided supportive evidence for the reliability of results.
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Linder, Martin. "Estimation of Evolutionary Divergence Times under Different Substitution Rate Models." Thesis, Uppsala University, Department of Mathematics, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-122052.
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Johansson, Ulf. "Obtaining Accurate and Comprehensible Data Mining Models : An Evolutionary Approach." Doctoral thesis, Linköping : Department of Computer and Information Science, Linköpings universitet, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8881.
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Galizia, Cosmas Giovanni. "Evolutionary models and phylogenetic inference : a morphometric study of insectivora." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284061.
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Vecchi, Davide. "Epistemological prospects of evolutionary models of the growth of knowledge." Thesis, London School of Economics and Political Science (University of London), 2006. http://etheses.lse.ac.uk/1915/.
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In the thesis I will argue that some models of evolutionary epistemology provide an extremely illuminating and original explanation of the workings of the scientific process. Evolutionary approaches to the growth of scientific knowledge have been criticised because of the putative existence of fundamental disanalogies between biological and scientific selective processes. I will show that these criticisms are largely misguided. I will distinguish two main kinds of evolutionary models. EEM models, which focus on the evolution of human cognitive mechanisms by natural selection (e.g. that developed by Ruse), do not provide a satisfactory basis on which to explain the nature of scientific selection processes, which are cultural rather than biological in origin. EET models, by contrast, focusing on the cultural and social origins of the selective systems operating in science, are better suited to this task. I will focus mainly on the EET models proposed by Donald Campbell and David Hull. Two general themes emerge from their analysis: the emphasis on the general validity of the variation-selection model of knowledge acquisition (i.e. trial-and-error), and the view that science is a socially adaptive and adapted system, governed by the action of peculiar selective mechanisms that partially lead to epistemic success. On the basis of the critical examination of these EET models I will argue for three main conclusions. First, EET approaches are correct in rejecting the methodological individualism so central to many alternative epistemologies. Second, EET models offer us genuinely normative epistemological insights, particularly where social epistemology is concerned. Third, EET provides a viable naturalistic alternative to social constructivism, by justifying epistemic standards as "evolutionary constructions" (i.e., products of selection processes).
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Wolff-Piggott, Timothy. "Identifying predictors of evolutionary dispersion with phylogeographic generalised linear models." Master's thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/25651.
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Discrete phylogeographic models enable the inference of the geographic history of biological organisms along phylogenetic trees. Frequently applied in the context of epidemiological modelling, phylogeographic generalised linear models were developed to allow for the evaluation of multiple predictors of spatial diffusion. The standard phylogeographic generalised linear model formulation, however, assumes that rates of spatial diffusion are a noiseless deterministic function of the set of covariates, admitting no other unobserved sources of variation. Under a variety of simulation scenarios, we demonstrate that the lack of a term modelling stochastic noise results in high false positive rates for predictors of spatial diffusion. We further show that the false positive rate can be controlled by including a random effect term, thus allowing unobserved sources of rate variation. Finally, we apply this random effects model to three recently published datasets and contrast the results of analysing these datasets with those obtained using the standard model. Our study demonstrates the prevalence of false positive results for predictors under the standard phylogeographic model in multiple simulation scenarios and, using empirical data from the literature, highlights the importance of a model accounting for random variation.
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Edenhofer, Ottmar. "Social conflict and technological change : evolutionary models of energy use /." [S.l. : s.n.], 1999. http://swbplus.bsz-bw.de/bsz115946934inh.pdf.
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Premo, L. S. "Agent-based models as behavioral laboratories for evolutionary anthropological research." University of Arizona, Department of Anthropology, 2006. http://hdl.handle.net/10150/110026.
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2006 Dozier Award WinnerAgent-based models can provide paleoanthropologists with a view of behavioral dynamics and site formation processes as they unfold in digital caricatures of past societies and paleoenvironments. This paper argues that the agent-based methodology has the most to offer when used to conduct controlled, repeatable experiments within the context of behavioral laboratories. To illustrate the potential of this decidedly heuristic approach, I provide a case study of a simple agent-based model currently being used to investigate the evolution of Plio-Pleistocene hominin food sharing in East Africa. The results of this null model demonstrate that certain levels of ecological patchiness can facilitate the evolution of even simple food sharing strategies among equally simple hominin foragers. More generally, they demonstrate the potential that agent-based models possess for helping historical scientists act as their own informants as to what could have happened in the past.
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Kobayashi, Yutaka. "Evolutionary models of talking plant hypotheses in a tritrophic context." 京都大学 (Kyoto University), 2004. http://hdl.handle.net/2433/147850.
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Thai, Doan Hoang Cau Australian Graduate School of Management Australian School of Business UNSW. "Analysing tacit collusion in oligopolistic electricity markets using a co-evolutionary approach." Awarded by:University of New South Wales. Australian Graduate School of Management, 2005. http://handle.unsw.edu.au/1959.4/22478.
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Wholesale electricity markets now operate in many countries around the world. These markets determine a spot price for electricity as the clearing price when generators bid in energy at various prices. As the trading in a wholesale electricity market can be seen as a dynamic repeated game, it would be expected that profit maximising generators learn to engage in tacit collusion to profitably increase spot market prices. This thesis investigates this tacit collusion of generators in oligopolistic electricity markets. We do not follow the approach of previous work in game theory that presupposes firms' collusive strategies to enforce collusion in an oligopoly. Instead, we develop a co-evolutionary approach (extending previous work in this area) using a genetic algorithm (GA) to co-evolve strategies for all generators in some stylised models of an electricity market. The bidding strategy of each generator is modelled as a set of bidding actions, one for each possible discrete state of the state space observed by the generator. The market trading interactions are simulated to determine the fitness of a particular strategy. The tacitly collusive outcomes and strategies emerging from computational experiments are thus obtained from the learning or evolutionary process instead of from any pre-specification. Analysing many of those emergent collusive outcomes and strategies. we are able to specify the mechanism of tacit collusion and investigate how the market environment can affect it. We find that the learned collusive strategies are similar to the forgiving trigger strategies of classical supergame theory (Green and Porter, 1984). Also using computational experiments, we can determine which characteristics of the market environment encourage or hinder tacit collusion. The findings from this thesis provide insights on tacit collusion in an oligopoly and policy implications from a learning perspective. With modelling flexibility, our co-evolutionary approach can be extended to study strategic behaviour in an oligopoly considering many other market characteristics.
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Ling, Kwok-tung, and 凌國棟. "Evolutionary optimisation of decision rules for production-distribution systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B3124449X.
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Lepage, Thomas. "The impact of variable evolutionary rates on phylogenetic inference : a Bayesian approach." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103264.
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In this dissertation, we explore the effect of variable evolutionary rates on phylogenetic inference. In the first half of the thesis are introduced the biological fundamentals and the statistical framework that will be used throughout the thesis. The basic concepts in phylogenetics and an overview of Bayesian inference are presented in Chapter 1. In Chapter 2, we survey the models that are already used for rate variation. We argue that the CIR process---a diffusion process widely used in finance---is the best suited for applications in phylogenetics, for both mathematical and computational reasons. Chapter 3 shows how evolutionary rate models are incorporated to DNA substitution models. We derive the general formulae for transition probabilities of substitutions when the rate is a continuous-time Markov chain, a diffusion process or a jump process (a diffusion process with discrete jumps).The second half of the thesis is dedicated to applications of variable evolutionary rate models in two different contexts. In Chapter 4, we use the CIR process to model heterotachy, an evolutionary hypothesis according to which positions of an alignment may evolve at rates that vary with time differently from site to site. A comparison the CIR process with the covarion---a widely-used heterotachous model---on two different data sets allows us to conclude that the CIR provides a significantly better fit. Our approach, based on a Bayesian mixture model, enables us to determine the level of heterotachy at each site. Finally, the impact of variable evolutionary rates on divergence time estimation is explored in Chapter 5.
Several models, including the CIR process are compared on three data sets. We find that autocorrelated models (including the CIR) provide the best fits.
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Birget, Philip Laurent Guillaume. "Evolutionary ecology of parasites : life-history traits, phenotypic plasticity, and reproductive strategies." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/28805.
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Adaptive phenotypic plasticity, the ability of a genotype to give rise to different phenotypes in different environments, evolves to allow organisms to fine-tune their life-history traits according to the varying conditions they encounter during their lives. Reproductive investment - the manner in which organisms divide their resources between survival and reproduction - is well studied in evolutionary ecology because it is a key determinant of fitness. However, whilst plasticity in reproductive effort is well understood for free-living multicellular taxa (such as insects, birds, and mammals), the application of evolutionary theory for plasticity and life history strategies to unicellular parasites and pathogens is lacking. In this thesis, I use empirical and theoretical approaches to uncover how differential resource allocation to non-replicating, sexual stages (gametocytes) versus asexually replicating stages can be harnessed by the rodent malaria parasite Plasmodium chabaudi to maximise its fitness across the often very variable conditions it encounters during infections. Differential allocation between those stages is equivalent to the fundamental life-history trade-off between survival and reproduction because gametocytes are responsible for between-host transmission (i.e. reproduction of the infection) whereas asexual parasites mediate host exploitation and within-host survival. A suite of within-host models reveal that malaria parasites could gain considerable fitness benefits in the face of low levels of drug treatment if they reduce their investment into gametocyte production ("reproductive restraint"), thereby assuring the continuity of the infection and capitalising on opportunities for future transmission. In contrast, high levels of drug treatment typically select parasites to commit all of their resources to gametocyte production ("terminal investment"), to escape a host that does not offer much opportunity for future transmission. My experiments reveal that P. chabaudi increases both its reproductive investment and its asexual replication rate in anaemic hosts (i.e. host that have a low density of red blood cells), suggesting that parasites profit from host anaemia and can afford high investment in gametocytes ("affluent investment"). I also uncover plasticity in a number of traits that underpin asexual replication rate, including invasion preference for different ages of red blood cells, but it is plasticity in the number of progeny (merozoites) per infected cell that is the main contributor to asexual replication rate. My experiments also reveal genetic variance in plasticity of the life-history traits investigated, which has profound implications for their evolution. Furthermore, plastic modification of these traits is associated with minimal costs or constraints, so that parasites can rapidly match life-history traits appropriately to the within-host environment. Severe anaemia is one of the deadliest symptoms of malaria, so observing that virulence and infectiousness increases in anaemic hosts has also fundamental clinical implications. Finally, the empirical and theoretical observations of affluent investment, reproductive restraint and terminal investment match theoretical predictions of how organisms should behave in varying environments, confirming P. chabaudi as a useful model system to test life-history theory.
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Luo, Hao, and 罗浩. "Hybrid flowshop scheduling with job interdependences using evolutionary computing approaches." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B47849551.
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This research deals with production scheduling of manufacturing systems that predominantly consist of hybrid flowshops. Hybrid Flowshop Scheduling (HFS) problems are common in metal working industries. Their solution has significant inferences on company performance in a globally competitive market in terms of production cycle time, delivery dates, warehouse and work-in-process inventory management. HFS problems have attracted considerable research efforts on examining their scientific complexity and practical solution algorithms. In conventional HFS systems, an individual job goes through the flowshop with its own processing route, which has no influence on other jobs. However, in many metal working HFS systems, jobs have interdependent relationships during the process. This thesis focuses on addressing two classes of HFS problems with job interdependence that have been motivated by real-life industrial problems observed from our collaborating companies.
The first class of HFS problems with job interdependence are faced by manufacturers of typically standard metal components where jobs are organized in families according to their machine settings and tools. Family setup times arise when a machine shifts from processing one job family to another. This problem is compounded by the challenges that the formation of job families is different in different stages and only a limited number of jobs can be processed within one setup. This class of problems is defined as HFS with family setup and inconsistent family formation.
The second class of HFS problems with job interdependence is typically faced in a production process consisting of divergent operations where a single input item is converted into multiple output items. Two important challenges have been investigated. One is that one product can be produced following different process routes. The other is that the total inventory capacity is very limited in the company in the sense that the inventory spaces are commonly shared by raw materials, work-in-process items and finished products. This class of problems is defined as HFS with divergent production and common inventory.
The aim is to analyze the general characteristics of HFS with job interdependence and develop effective and practical methodologies that can tackle real-world constraints and reduce the scheduling effort in daily production.
This research has made the following contributions: (1) A V-A-X structural classification has been proposed to represent the divergent (V), convergent (A) and mixed (X) job interdependent relations during the production. (2) A genetic algorithm based approach and a particle swarm optimization based approach have been developed to solve two classes of HFS problems with job interdependence, respectively. The computational results based on actual production data have shown that the proposed solutions are robust, efficient and advantageous for solving the practical problems. (3) A waiting factor approach and delay timetable approach have been developed to extend the solutions space of two classes of HFS problems by inserting intentional idle times into original schedules. The computational results have indicated that better schedules can be obtained in the extended solution spaces.published_or_final_version
Industrial and Manufacturing Systems Engineering
Doctoral
Doctor of Philosophy
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Hallier, Mareen [Verfasser]. "Formalization and Metastability Analysis of Agent-Based Evolutionary Models / Mareen Hallier." Berlin : Freie Universität Berlin, 2015. http://d-nb.info/1068809965/34.
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