Tesis sobre el tema "Trade-off optimization"

The focus of this dissertation is on improving decision-maker trade-offs and the development of a new constrained methodology for multiple response surface optimization. There are three key components of the research: development of the necessary conditions and assumptions associated with constrained multiple response surface optimization methodologies; development of a new constrained multiple response surface methodology; and demonstration of the new method. The necessary conditions for and assumptions associated with constrained multiple response surface optimization methods were identified and found to be less restrictive than requirements previously described in the literature. The conditions and assumptions required for a constrained method to find the most preferred non-dominated solution are to generate non-dominated solutions and to generate solutions consistent with decision-maker preferences among the response objectives. Additionally, if a Lagrangian constrained method is used, the preservation of convexity is required in order to be able to generate all non-dominated solutions. The conditions required for constrained methods are significantly fewer than those required for combined methods. Most of the existing constrained methodologies do not incorporate any provision for a decision-maker to explicitly determine the relative importance of the multiple objectives. Research into the larger area of multi-criteria decision-making identified the interactive surrogate worth trade-off algorithm as a potential methodology that would provide that capability in multiple response surface optimization problems. The ISWT algorithm uses an ε-constraint formulation to guarantee a non-dominated solution, and then interacts with the decision-maker after each iteration to determine the preference of the decision-maker in trading-off the value of the primary response for an increase in value of a secondary response. The current research modified the ISWT algorithm to develop a new constrained multiple response surface methodology that explicitly accounts for decision-maker preferences. The new Modified ISWT (MISWT) method maintains the essence of the original method while taking advantage of the specific properties of multiple response surface problems to simplify the application of the method. The MISWT is an accessible computer-based implementation of the ISWT. Five test problems from the multiple response surface optimization literature were used to demonstrate the new methodology. It was shown that this methodology can handle a variety of types and numbers of responses and independent variables. Furthermore, it was demonstrated that the methodology can be successful using a priori information from the decision-maker about bounds or targets or can use the extreme values obtained from the region of operability. In all cases, the methodology explicitly considered decision-maker preferences and provided non-dominated solutions. The contribution of this method is the removal of implicit assumptions and includes the decision-maker in explicit trade-offs among multiple objectives or responses.
Ph.D.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering PhD

Forest is a resource that is increasingly utilized for multiple purposes. The balance between energy demands and the long-term capacity of ecosystems to support biodiversity and other ecosystem services is crucial. The aim of this project was to increase the knowledge on and to develop methods and tools for trade-offs and synergies analysis among forest ecosystem services based on different forest management policies. Paper I provides an overview of existing models for integrated energy-environment assessment. A literature review was conducted on assessment models and their ability to integrate energy with environmental aspects. Missing environmental aspects concern land use, landscapes and biodiversity. In Paper II a modelling framework was set up to link a landscape simulator with a habitat network model for integrated assessment of bioenergy feedstock and biodiversity related impacts in Kronoberg County. In Paper III we continued with the same management scenarios, while the analysis was expanded to five ecosystem services by developing the Landscape simulation and Ecological Assessment (LEcA) tool: industrial wood, bioenergy, forest carbon stock, recreation areas and habitat networks. In Paper IV we present two heuristic methods for spatial optimization – simulated annealing (SA) and genetic algorithm (GA) – to find optimal solutions for allocating harvest activities, in order to minimize the impacts on habitat networks. In Paper V, as response to the findings in Paper I, we linked the energy model MESSAGE with our LEcA tool for forest bioenergy demand assessment while applying environmental and transport restrictions, in a study of Lithuania. We found trade-offs between industrial wood production and bioenergy on one side, and recreation values, biodiversity, and to some extent carbon storage on the other side. The LEcA tool integrated forest simulation and management with assessment of ecosystem services, which is promising for integrated sustainability assessment of forest management policies.

QC 20171023

In this thesis, meta-heuristic algorithms are developed to obtain optimum or near optimum solutions for the time-cost-resource trade-off and resource leveling problems in project scheduling. Time cost trade-off, resource leveling, single-mode resource constrained project scheduling, multi-mode resource constrained project scheduling and resource constrained time cost trade-off problems are analyzed. Genetic algorithm simulated annealing, quantum simulated annealing, memetic algorithm, variable neighborhood search, particle swarm optimization, ant colony optimization and electromagnetic scatter search meta-heuristic algorithms are implemented for time cost trade-off problems with unlimited resources. In this thesis, three new meta-heuristic algorithms are developed by embedding meta-heuristic algorithms in each other. Hybrid genetic algorithm with simulated annealing presents the best results for time cost trade-off. Resource leveling problem is analyzed by five genetic algorithm based meta-heuristic algorithms. Apart from simple genetic algorithm, four meta-heuristic algorithms obtained same schedules obtained in the literature. In addition to this, in one of the test problems the solution is improved by the four meta-heuristic algorithms. For the resource constrained scheduling problems
genetic algorithm, genetic algorithm with simulated annealing, hybrid genetic algorithm with simulated annealing and particle swarm optimization meta-heuristic algorithms are implemented. The algorithms are tested by using the project sets of Kolisch and Sprecher (1996). Genetic algorithm with simulated annealing and hybrid genetic algorithm simulated annealing algorithm obtained very successful results when compared with the previous state of the art algorithms. 120-activity multi-mode problem set is produced by using the single mode problem set of Kolisch and Sprecher (1996) for the analysis of resource constrained time cost trade-off problem. Genetic algorithm with simulated annealing presented the least total project cost.

In pursuance of decreasing costs, both the client and the contractor would strive to speed up the construction project. However, accelerating the project schedule will impose additional cost and might be profitable up to a certain limit. Paramount for construction management, analyses of this trade-off between duration and cost is hailed as the time-cost trade-off (TCT) optimization. Inadequacies of existing commercial software packages for such analyses tied with eminence of discretization, motivated development of different paradigms of particle swarm optimizers (PSO) for three extensions of discrete TCT problems (DTCTPs). A sole-PSO algorithm for concomitant minimization of time and cost is proposed which involves minimal adjustments to shift focus to the completion deadline problem. A hybrid model is also developed to unravel the time-cost curve extension of DCTCPs. Engaging novel principles for evaluation of cost-slopes, and pbest/gbest positions, the hybrid SAM-PSO model combines complementary strengths of overhauled versions of the Siemens Approximation Method (SAM) and the PSO algorithm. Effectiveness and efficiency of the proposed algorithms are validated employing instances derived from the literature. Throughout computational experiments, mixed integer programming technique is implemented to introduce the optimal non-dominated fronts of two specific benchmark problems for the very first time in the literature. Another chief contribution of this thesis can be depicted as potency of SAM-PSO model in locating the entire Pareto fronts of the practiced instances, within acceptable time-frames with reasonable deviations from the optima. Possible further improvements and applications of SAM-PSO model are suggested in the conclusion.

Road collisions negatively affect the lives of hundreds of Canadians per year. Unfortunately, safety has been typically neglected from management systems. It is common to find that a great deal of effort has been devoted to develop and implement systems capable of achieving and sustaining good levels of condition. It is relatively recent that road safety has become an important objective. Managing a network of roads is not an easy task; it requires long, medium and short term plans to maintain, rehabilitate and upgrade aging assets, reduce and mitigate accident exposure, likelihood and severity. This thesis presents a basis for incorporating road safety into road management systems; two case studies were developed; one limited by available data and another from sufficient information. A long term analysis was used to allocate improvements for condition and safety of roads and bridges, at the network level. It was confirmed that a safety index could be used to obtain a first cut model; meanwhile potential for improvement which is a difference between observed and predicted number of accidents was capable of capturing the degree of safety of individual segments. It was found that the completeness of the system resulted in savings because of the economies obtained from trade-off optimization. It was observed that safety improvements were allocated at the beginning of the analysis in order to reduce the extent of issues, which translated into a systematic reduction of potential for improvement up to a point of near constant levels, which were hypothesized to relate to those unavoidable collisions from human error or vehicle failure.

Renewable energy sources (RESs) are considered as the most reliable option in the terms of reducing CO2 emission. RESs are known by their low operation and maintenance (O&M) cost and easier installation. In the previous years, their reliability was less due to their uncertainty; however, in the modern days, it is possible to limit RES fluctuations by recently developed technologies such as optimization tools and precise forecasting algorithms. RESs are not always preferred in case studies where the fossil fuels are extremely cheap. In such countries, investors prefer to implement gas turbines or diesel generators regardless of the penalty associated with their negative impacts of such plants on the environmental. Many countries that have low fuel cost are going forward with expanding the conventional power systems with a low growth towards the hybrid renewable power system. This would increase the reliance on sources such as fossil fuels which diminish over time. Moreover, many environmental benefits of the hybrid renewable energy systems (HRES) would not be achieved in which it will be harmful to the environment. Therefore, a trade-off solution is proposed towards solving this problem in which it would make a balance between cost and CO2 emissions. To this end, in this thesis, the objective is to find a reasonable solution (i.e., trade-off) between the cost and the emission. To find such a trade-off, an optimization software called “HOMER Pro” is utilized to identify the optimal design. A compromised solution will be identified with low CO2 emission and low net present cost (NPC). Saudi Arabian Wasit Gas Plant (WGP) owned by Saudi Aramco Company, which is located in a remote area of the country, is chosen as the case study of this thesis. A photovoltaic (PV), wind turbine, reformer, battery, hydrogen tank, and fuel cells are considered to be implemented on the investigated case study.

The purpose of this thesis is to investigate to what extent the environmental agenda should be taken into consideration during the project phase of logistics at Northvolt. The objective is to build an optimization model for route planning with a trade-off solution for three criteria; cost, emission and time. An abductive research approach is used. The empirical data was collected quantitatively in accordance with cross-industry standard process for data mining. The results obtained from the optimization model were based on an emission calculation framework and weights assigned to the three selected criteria by five decision makers. These results are compared to an as-is analysis of current and of historical transportations as well as to expected future transportations. These results provide insights and emphasize the importance of agility in decision making aiming at the reduction of emissions. The analysis shows that increased costs do not have a clear correlation with reduced emissions or transportation time. It also demonstrates that transporting goods on sea would increase the transportation time but decrease the emissions. The conclusions of the study are that costs can be reduced by 8%, emissions by 6% and transportation time by 14%, compared to their current operations. Short-term recommendations address the need of being agile in the route planning and analyse each shipment individually where the weights of the criteria should be alternated depending on the status of the project. This requires increased communication with the installation team on site and negotiation of contractual rates from additional ports in Sweden. Long-term recommendations emphasise the importance of developing and using emission key performance indicators to set targets in combination with a strategy in order to steer daily operations.

This study is conducted with the aims to develop a new ranking method for multi-criteria decision making problem with conflicting criteria. Such a problem has a set of Pareto solutions, where the act of improving a value of one solution will result in depreciating some of the others. Thus, in this type of problem, there is no unique solution. However, out of many available options, the Decision Maker eventually has to choose only one solution. With this problem as the motivation, the current study develops a compromise ranking algorithm, namely a trade-off ranking method. The trade-off ranking method able to give a trade-off solution with the least compromise compared to other choices as the best solution. The properties of the algorithm are studied in the thesis on several test cases. The proposed method is compared against several multi-criteria decision making methods with ranking based on the distance measure, which are the TOPSIS, relative distance and VIKOR. The sensitivity analysis and uncertainty test are carried out to examine the methods robustness. A critical criteria analysis is also done to test for the most critical criterion in a multi-criteria problem. The decision making method is considered further in a fuzzy environment problem where the fuzzy trade-off ranking is developed and compared against existing fuzzy decision making methods.

The present work deals with the study and analysis of the simultaneous optimization of time, cost and quality by using artificial intelligence technique; The approach is based on the use of genetic algorithms implemented in Matlab applied to a case study, the construction of a new University Campus in Cesena, focusing on the external walls of the building itself. The objective is to find a set of optimal solutions, equally valid, for the realization of stratigraphies of the different types of external masonry; It will then be the task of the designer to choose among possible solutions which he believes to be most appropriate, based on the requirements of the project, which may be in terms of quality, cost, time or a combination of two or more of these evaluation parameters. It will thus illustrate how different solutions provided by the program can be used and collected in a three-dimensional graph.

The Earth harbors around 300 000 plant species. The rich and complex environment provided by plants is considered a key factor for the extraordinary diversity of the terrestrial fauna by, for example, providing food and shelter. This thesis contributes to the understanding of these questions by investigating how the interplay of physiology, demography, and evolution gives rise to variation and diversity in fundamental plant traits. This will help us answer questions such as: How has this amazing diversity of plant species emerged? Which mechanisms maintain diversity? How are plant strategies and plant diversity influenced by variations in the environment? A plant faces multiple problems to survive and reproduce successfully. These problems can be modeled by considering traits, trade-offs and a fitness measure. For example: How to maximize growth rate, while maximizing structural stability? I will investigate four plant models in order to understand the function of plants, and mechanisms promoting diversity.  Paper I: We study how annual plants with and without growth constraints should optimize their flowering time when productivity or season length changes. With a dynamic ontogenetic growth model and optimal control theory we prove that a bang-bang reproductive control is optimal under constrained growth and constant mortality rate. We find that growth constraints can flip the direction of optimal phenological response for increasing productivity. The reason is that the growth rate of vegetative mass saturates at high productivity and therefore it is better to flower earlier and take advantage of a longer reproductive period. If season length extends equally both in the beginning and the end of the season, growth constraints control the direction of the optimal response as well. Our theory can help explaining phenological patterns along productivity gradients, and can be linked to empirical observations made on a calendar scale. Paper II: We introduce a new measure of tree crown-rise efficiency based on the loss of biomass of the tree during growth. The more mass the tree looses during growth, the less crown-rise efficient it is. Top-heavy shapes loose more biomass than bottom-heavy shapes. Light-use efficiency is defined as the mean light assimilation of the leaves in the crown times the ratio of leaf mass and total mass. We then study the trade-off between light-use efficiency to crown-rise efficiency for tree crown shapes. We assume that the total tree mass is constant, and a constant vertical light gradient represent the shading from a surrounding forest. We find large differences in crown shapes at intermediate vertical light gradient, when both self-shading and mean-field shading are important, suggesting light-use vs crown-rise efficiency as a new trade-off that can explain tree diversity. Our crown-rise efficiency measure could easily be integrated into existing forest models. Paper III: We extend an evolutionary tree crown model, where trees with different heights compete for light, with drought-induced mortality rates depending on ground-water availability and the depth of an optional taproot. The model does not include competition for ground water. Our model explains how ground-water availability can shape plant communities, when taproot and non-taproot strategies can coexist, and when only one of these strategies can persist. We investigate how emerging plant diversity varies with water table depth, soil water gradient and drought-induced mortality rate. The taproot enables plants to reach deep water, thus reducing mortality, but also carries a construction cost, thus inducing a trade-off. We find that taproots maintain plant diversity under increasing drought mortality, and that taproots evolve when groundwater is accessible at low depths. There are no viable strategies at high drought mortality and deep water table. Red Queen evolutionary dynamics appear at intermediate drought mortality in mixed communities with and without taproots, as the community never reaches a final evolutionarily stable composition. Paper IV: We extend a size-structured plant model, with self-shading and two evolving traits, crown top-heaviness and crown width-to-height ratio. The model allows us to identify salient trade-offs for the crown shape. The most important trade-off for top-heaviness is light-use efficiency vs crownrise efficiency, and the most important trade-off for width-to-height ratio is self-shading vs branch costs. We find that when the two traits coevolve; the outcome is a single common evolutionarily stable strategy (ESS), far away from the highest net primary production (NPP). When only sun angle is decreasing with increasing latitude both the crown width-to-height ratio and crown top-heaviness decrease. However, when light response in addition to the sun angle decreases with increasing latitude, the crown width-to-height ratio is nearly invariant of latitude except at low site productivity when the ratio decreases with latitude. Top-heaviness is always decreasing with increasing latitude. Finally, we find that crown top-heaviness increases with the NPP or leaf-area index (LAI) at ESS, but crown width-to-height ratio is maximal at an intermediate NPP or LAI.
Artikel I: Arters reproduktionsframgång (fitness), till exempel antal avkommor eller frön som produceras under livet, är ofta avgörande för huruvida de är evolutionärt framgångsrika eller inte. Här undersöker vi hur ettåriga växter med eller utan tillväxtbegränsningar ska optimera sin blomningstid när produktivitet eller säsongslängd ändras. Det är optimalt att gå direkt från tillväxt till blomning när tillväxten är begränsad och dödligheten är konstant. Vid ökad produktivitet sker blomningen tidigare med tillväxtbegränsningar men senare utan tillväxtbegränsningar, vilket beror på att med tillväxtbegränsningar ökar den vegetativa massan långsamt. Därför är det bättre att blomma tidigare och ta tillvara på en längre reproduktionsperiod. Vi får samma resultat om säsongslängden ökar lika mycket i början och slutet av säsongen. Vår teori kan bidra till att förutsäga blomningstider vid produktivitetsförändringar och säsongsförändringar. Artikel II: Tillväxten hos träd kan begränsas av brist på ljus, vatten, och näring, men också genom förlust av grenar. Vi introducerar ett nytt mått på tillväxteffektiviteten hos trädkronor baserat på förlust av biomassa under trädets tillväxt. Ju mer massa trädet förlorar under tillväxt, desto mindre tillväxteffektiva är de. Topptunga former förlorar mer biomassa än bottentunga former. Vi studerar avvägningar mellan ljuseffektivitet och tillväxteffektivitet för trädformer, där ljuseffektiviteten definieras som medelljusupptaget för löven i kronan. Vi antar en konstant totalmassa, och en statisk vertikal skuggning som representerar skuggningen från en omgivande skog. Vi hittar stora skillnader i kronformer vid en medelhög skuggning, då både självskuggningen och medelskuggningen har betydelse. Vårt mått för tillväxteffektivitet kan enkelt integreras i existerande skogsmodeller. Studien visar att avvägningar mellan tillväxteffektivitet och ljuseffektivitetet kan vara viktig för mångfalden av trädformer i en skog. En överraskande upptäckt är att konformade eller sfäriska trädkronor aldrig är effektiva, men däremot timglasformade kronor. Artikel III: Växter kan försvara sig på olika sätt mot torka, till exempel genom att rulla ihop bladen eller genom att reproducera tidigare och därigenom undvika uttdragen torka. Här undersöker vi fördelarna med en pålrot vid torka. En pålrot är en rot som växer nedåt för att nå djupliggande grundvatten. Vi utvidgar en evolutionär modell av trädkronor med grundvatten och en pålrot, där träd med olika höjd konkurrerar om ljus. Det finns ingen konkurrens om vatten. Vi undersöker hur mångfalden hos träden beror på vattendjup, vattengradient och dödlighet orsakad av torka. Med hjälp av pålroten kan träden nå djupt vatten och därigenom minska dödligheten, men den medför också en kostnad, så en avvägning måste göras. Vi ser att pålrötter upprätthåller mångfalden hos växterna vid ökad mortalitet, och att pålrötter uppstår när grundvattnet är grunt. Det finns inga strategier som kan överleva om grundvattnet är djupt och dödligheten är hög. Vår modell kan förklara hur grundvatten kan förändra sammansättningen på trädsamhällen, när träd med och utan pålrot kan samexistera, och under vilka förutsättningar endast en av strategierna förväntas dominera. Artikel IV: Träd som växer upp i en skog måste konkurrera med andra träd om ljus, framförallt större träd. Detta ger upphov till en asymmetrisk ljuskonkurrens, där de små träden hämmas av större träd. Små träd har därmed små chanser att överleva utom då skogen nyligen störts och det öppnas upp en glänta. Vid denna ljuskonkurrens kan man anta att trädkronans form har stor betydelse för trädets framgång. Frågan är hur de evolutionärt fördelaktiga kronformerna beror på latituden och produktiviteten. Vi antar att latituden påverkar solens genomsnittliga vinkel och ljusrespons. Vi utvidgar en storleksstrukturerad trädmodell med självskuggning där två evolverande egenskaper beskriver kronans topptyngd och bredd. Med modellen kan vi undersöka vilka strategiska avvägningar som bestämmer om kronans form blir konkurrenskraftig. En topptung krona har högt ljusupptag eftersom det finns mest ljus högt upp i grenverket. Å andra sidan har den en låg tillväxteffektivitet eftersom topptunga kronor måste tappa mycket grenar för att behålla sin form. En bred krona har en låg självskuggning eftersom bladen är utspridda. Å andra sidan har den höga kostnader för de långa grenar som krävs. Vi finner att när dessa egenskaper evolverar tillsammans så finns endast en evolutionärt stabil strategi (ESS), långt från den högsta nettoproduktionen. När endast solvinkeln minskar med ökande latitud minskar både kronans bredd och topptyngd, men när både solvinkel och ljusrespons minskar med ökande latitud så är bredden nästan oförändrad utom vid låg produktivitet då den minskar med latituden. Kronans topptyngd minskar alltid med latituden. Slutligen ser vi hur kronans topptyngd alltid ökar med nettoproduktionen vid ESS, medan kronans bredd har ett maxium för ett mellanvärde hos nettoproduktionen vid ESS.

Este estudo considera o modelo de controle ótimo estocástico sob um critério de média-variância para sistemas lineares a tempo discreto sujeitos a saltos Markovianos e ruídos multiplicativos sob dois critérios. Inicialmente, consideramos como critério de desempenho a minimização multiperíodo de uma combinação entre a média e a variância da saída do sistema sem restrições. Em seguida, consideramos o critério de minimização multiperíodo da variância da saída do sistema ao longo do tempo com restrições sobre o valor esperado mínimo. Condições necessárias e suficientes explícitas para a existência de um controle ótimo são determinadas generalizando resultados anteriores existentes na literatura. O controle ótimo é escrito como uma realimentação de estado adicionado de um termo constante. Esta solução é obtida através de um conjunto de equações generalizadas a diferenças de Riccati interconectadas com um conjunto de equações lineares recursivas. Como aplicação, apresentamos alguns exemplos numéricos práticos para um problema de seleção de portfólio multiperíodo com mudança de regime, incluindo uma estratégia de ALM (Asset and Liability Management). Neste problema, deseja-se obter a melhor alocação de portfólio de forma a otimizar seu desempenho entre risco e retorno em cada passo de tempo até o nal do horizonte de investimento e sob um dos dois critérios citados acima.
In this work we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under two criterions. First, we consider an unconstrained multiperiod mean-variance trade-off performance criterion. In the sequence, we consider a multiperiod minimum variance criterion subject to constraints on the minimum expected output along the time. We present explicit necessary and sufficient conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. The optimal control law is written as a state feedback added with a deterministic sequence. This solution is derived from a set of coupled generalized Riccati difference equations interconnected with a set of coupled linear recursive equations. As an application, we present some practical numerical examples on a multiperiod portfolio selection problem with regime switching, including an Asset and Liability Management strategy. In this problem it is desired to nd the best portfolio allocation in order to optimize its risk-return performance in every time step along the investment horizon, under one of the two criterions stated above.In this work we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under two criterions. First, we consider an unconstrained multiperiod mean-variance trade-off performance criterion. In the sequence, we consider a multiperiod minimum variance criterion subject to constraints on the minimum expected output along the time. We present explicit necessary and sufficient conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. The optimal control law is written as a state feedback added with a deterministic sequence. This solution is derived from a set of coupled generalized Riccati difference equations interconnected with a set of coupled linear recursive equations. As an application, we present some practical numerical examples on a multiperiod portfolio selection problem with regime switching, including an Asset and Liability Management strategy. In this problem it is desired to nd the best portfolio allocation in order to optimize its risk-return performance in every time step along the investment horizon, under one of the two criterions stated above.

The phenomenon of financial bubbles is known to have impacted various markets since the seventeenth century. Such bubbles are known to form when the market drastically overvalues the price of an asset, causing its market value to increase hyperbolically, only to suddenly collapse once the untenable perceived future prospects of the asset are realized. Hence, it remains crucial for investors to be able to sell off assets residing within a bubble before they burst and their value is significantly diminished. Thus, portfolio optimization methods capable of accounting for financial bubbles in stock dynamics is a field of great value and interest for market participants. Portfolio optimization with respect to the mean-field is a relatively novel approach to accounting for the bubble-phenomenon. Hence, this paper investigates a previously unattempted method of portfolio optimization, providing a mean-field solution to the mean-variance trade-off problem, as well as providing new definitions of stock dynamics capable of diverting investors from bubbles.
Finansiella bubblor är ett fenomen som har påverkat marknader sedan 1600-talet. Bubblor tenderar att skapas när marknaden kraftigt övervärderar en tillgång vilket orsakar en hyperbolisk tillväxt i marknadspriset. Detta följs av en plötslig kollaps. Därför är det viktigt för investerare att kunna minska sin exponering mot aktier som befinner sig i en bubbla, så att risken för stora plötsliga förluster reduceras. Således är portföljoptimering där aktiedynamiken tar hänsyn till bubblor av högt intresse för marknadsdeltagare. Portföljoptimering med avseende på medelfältet är ett relativt nytt tillvägagångssätt för att behandla bubbelfenomen. Av denna anledning undersöks i detta arbete en hittills oprövad lösningsmetod som möjliggör en medelfältslösning till avvägningen mellan förväntad avkastning och risk. Där-utöver presenteras även ett antal nya modeller för aktier som kan bortleda investerare från bubblor.

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Universidade Federal de Minas Gerais
The management of manufacturing systems have become more complex, once that new products are arising, product demands are uncertain, life cycles get shorter, and a wide variety of products compete for common resources. This thesis deals with the design and planning of discrete manufacturing systems, based on open queueing network models to support the decision making of capacity allocation. As manufacturing systems may be represented by generalized queueing networks, and there are no exact solution methods, here is employed the decomposition approximate method to evaluate the performance of systems under different configurations. It is shown in the thesis how these approximations are suitable and effective to estimate the work-in-process (WIP) and the production leadtime of an actual metallurgical industry queueing network. It is also shown that discrete capacity allocation models, based on the approximations, are effective to evaluate and optimize the performance of the case study under different configurations. Trade-off curves between capacity investment and WIP are generated and are useful not only to support a manager to estimate how much capacity he/she should allocate, but also to decide where it should be allocated in the queueing network. These curves also support the decision making in terms of capacity, if the variability of the external arrivals, the product mix and/or the throughput for the network change. Besides adding capacity, partitioning the facility is another alternative to reduce the system complexity. This thesis also approaches the focused factory design problem, involving the partition of the facility into smaller shops and the capacity allocation in each shop. Again, the decomposition approximations were employed to evaluate the system performance. Despite its importance, this problem has rarely been reported in the literature. In this thesis, the goal is to reduce the system complexity either from the product management point of view or from the workstation management point of view. From the product management point of view, a model whose complexity constraint is na upper limit on the production leadtime variance of the products passing through the network was studied. From the workstation management point of view, the complexity constraint of the model keeps constant the expected waiting time of a product at a workstation, once it waits for being served. It is shown through these models for some instances that the partition of the facility into smaller shops decreases the complexity system without necessary capacity additional investments. Futhermore, sometimes it is possible to keep the network performance (or even to improve it), partitioning the network into smaller shops which need less capacity than the original configuration with a single shop.
A gestão de sistemas de manufatura tem se tornado mais complexa na medida em que novos produtos estão surgindo, a demanda de produtos é incerta, os ciclos de vida são mais curtos e uma grande variedade de produtos competem pelos mesmos recursos. Esta tese trata o projeto e planejamento de sistemas discretos de manufatura, baseados em modelos de redes de filas abertas, para auxiliar no processo de tomada de decisões. Porque sistemas de manufatura podem ser representados por redes de filas genéricas, e não existem métodos exatos de solução, aqui é empregado o método aproximado de decomposição para avaliar o desempenho dos sistemas em diferentes configurações. Mostra-se nesta tese que estas aproximações são adequadas e efetivas para estimar os estoques em processo (WIP) e o leadtime de produção de uma rede de manufatura real de uma indústria metal-mecânica. Mostra-se ainda que os modelos de alocação de capacidade discreta, baseados nestas aproximações, também são efetivos para avaliar e otimizar o desempenho da rede do estudo de caso em diferentes configurações. Curvas de trade-off entre investimento em capacidade e WIP são geradas e são úteis não somente para auxiliar um gerente a estimar quanto alocar de capacidade, mas também para decidir onde alocá-la na rede de filas. As curvas também auxiliam a tomada de decisões em termos de capacidade, se a variabilidade das chegadas externas, o mix de produtos e/ou a taxa de produção da rede mudam. Além de adicionar capacidade, a partição da instalação é outra alternativa para reduzir a complexidade do sistema. Esta tese também aborda o problema de projeto de fábrica focalizada, envolvendo a partição da instalação em subplantas e a alocação de capacidade em cada estação das subplantas. Novamente, as aproximações por decomposição foram utilizadas para avaliar e otimizar o desempenho do sistema. Apesar de sua importância, este problema tem sido muito pouco reportado em literatura. Nesta tese, o objetivo é reduzir a complexidade do sistema do ponto de vista da gestão do produto, ou do ponto de vista da gestão da estação. Do ponto de vista da gestão do produto, é apresentado um modelo cuja restrição de complexidade é um limitante superior para a variância do leadtime dos produtos na rede. Do ponto de vista da gestão da estação, a restrição de complexidade do modelo fixa o tempo médio de espera de um produto na estação, quando há espera. Mostra-se, por meio destes modelos para alguns casos que, a partição da instalação em subplantas reduz a complexidade do sistema, sem necessidade de investimentos adicionais em capacidade. Além disso, algumas vezes, é possível manter (ou até melhorar) o desempenho da rede, particionando-a em subplantas que necessitam de menos capacidade do que a configuração original com uma planta única.

L'utilisation des modèles 3D, représentés sous forme de maillage, est sans cesse croissante dans de nombreuses applications. Pour une transmission efficace et pour une adaptation à l'hétérogénéité des ressources de ces modèles, des techniques de compression progressive sont généralement utilisées. Afin de protéger le droit d'auteur de ces modèles pendant la transmission, des techniques de tatouage sont également employées. Dans ces travaux de thèse, nous proposons premièrement deux méthodes de compression progressive pour des maillages avec ou sans information de couleurs et nous présentons finalement un système conjoint de compression progressive et de tatouage. Dans une première partie, nous proposons une méthode d'optimisation du compromis débit-distorsion pour des maillages sans attribut de couleur. Pendant le processus de l'encodage, nous adoptons la précision de quantification au nombre d'éléments et à la complexité géométrique pour chaque niveau de détail. Cette adaptation peut s'effectuer de manière optimale en mesurant la distance par rapport au maillage original, ou de façon quasi-optimale en utilisant un modèle théorique pour une optimisation rapide. Les résultats montrent que notre méthode donne des résultats compétitifs par rapport aux méthodes de l'état de l'art. Dans une deuxième partie, nous nous focalisons sur l'optimisation du compromis débit-distorsion pour des maillages possédant l'information de couleur attachée aux sommets. Après avoir proposé deux méthodes de compression pour ce type de maillage, nous présentons une méthode d'optimisation du débit-distorsion qui repose sur l'adaptation de la précision de quantification de la géométrie et de la couleur pour chaque maillage intermédiaire. Cette adaptation peut être effectuée rapidement selon un modèle théorique qui permet d'évaluer le nombre de bits de quantification nécessaire pour chaque maillage intermédiaire. Une métrique est également proposée pour préserver les éléments caractéristiques durant la phase de simplification. Finalement, nous proposons un schéma conjoint de compression progressive et de tatouage. Afin de protéger tous les niveaux de détails, nous insérons le tatouage dans chaque étape du processus d'encodage. Pour cela, à chaque itération de la simplification, nous séparons les sommets du maillage en deux ensembles et nous calculons un histogramme de distribution de normes pour chacun d'entre eux. Ensuite, nous divisons ces histogrammes en plusieurs classes et nous modifions ces histogrammes en décalant les classes pour insérer un bit. Cette technique de tatouage est réversible et permet de restaurer de manière exacte le maillage original en éliminant la déformation induite par l'insertion du tatouage. Nous proposons également une nouvelle méthode de prédiction de la géométrie afin de réduire le surcoût provoqué par l'insertion du tatouage. Les résultats expérimentaux montrent que notre méthode est robuste à diverses attaques géométriques tout en maintenant un bon taux de compression

碩士
國立交通大學
土木工程系所
102
Optimization problems in time-cost trade-off (TCTO) analysis of construction management have been traditionally solved by two distinctive approaches: heuristic methods and optimization techniques. Although heuristic methods can handle large-size projects, they do not guarantee optimal solutions. Recently, artificial intelligence (AI) techniques such as genetic algorithms (GAs), ant colony optimization (ACO), and particle swarm optimization (PSO) have been introduced to overcome the problems associated with (1) large number of variables and constraints; (2) non linearity of time-cost functions; and (3) multi-objective optimization. Traditional time-cost trade-off (TCTO) analysis of construction management assumes the constant value of activities’ cost along the project time span. In fact, the value of money decreases with time or in other words, disregard time value of money. Therefore, discounted cash flows should be considered when solving TCTO optimization problems. Furthermore, in reality, due to different uncertainty, the actual cost of each option is also not known by the manager in advance as a risk. Hence, the total cost of the project may significantly because of these uncertainty. Unfortunately, traditional TCTO analysis also disregards this factor. This study tries to incorporate time value of money and uncertainty into TCTO analysis. Details of model formulation are illustrated by an example project. The model has the following features: (1) optimum solution is guaranteed; (2) precise discrete activity time-cost relationship is used; (3) time value of money is taken into consideration; and (4) uncertainty in the project also are involved. The results show that inclusion of discounted cash flow results in distinct optimal project duration. Nevertheless, through the Monte Carlo simulation, which is in order to involve uncertainty, this proposed model also lead to distinct optimal duration at the certain percentile level. The proposed model for this study can help the practitioners in considering time value of money and uncertainty cost, in order to make the best time-cost decision and to identify risks involved.

博士
國立臺灣大學
生物環境系統工程學研究所
103
Urbanization significantly drives land conversion and therefore may take up additional 1.8% of all biological hotspot areas by 2030. On the other hand, the establishment of protected areas for biological conservation often limits urban development. However, previous land use allocation models rarely take into account synergistic balance between urban development and biological conservation. This study develops a multi-objective spatial optimization model based on the cell-based Dynamically Dimensioned Search Landscape Optimization Planning Model for maximizing the consequential urban development suitability and habitat quality of resultant land-use patterns. As such, the trade-off between urban development and biological conservation can be revealed for assessing restorability and urbanization potential of planning areas in developing regional planning strategies. The model was applied to the Taipei-Taoyuan area for evaluating the conservation-development initiatives which maximize different weighted sums of suitabilities in accordance with the preferred landscape structures for buildings and the Taiwan Barbet. The results identified a number of cropland areas which had high urbanization potential and low habitat restorability for the target species, therefore these areas were suggested to be converted to urban land use. On the other hand, urban planning areas determined as a marginal habitat (i.e. high restorability) can be rezoned to fit the conservation needs as long as massive reforestation efforts were undertaken. The results showed that high restorability urban planning areas can be rezoned to fit the conservation needs. In doing so, green space can penetrate into the urban area from an ecological perspective. Furthermore, the study also revealed that spatial optimization at a cellular level can enhance habitat structures at a finer resolution compared to patch-level landscape optimization. The findings provide insights into the applications of optimal landscape patterns for not only regional rezoning but also built environment design.

Equitable water allocation in the context of local-scale water conflicts can be very challenging. This study aimed at providing new perspectives to the analysis of local water conflict with a special focus on two issues. First, the most vulnerable communities, who face the largest risk from unbalanced water management decisions, are often devoid of any technical and scientific support. And second, ecosystem services are hardly took into account when it comes to water allocation decision-making. We present a holistic framework for the analysis of small-scale water disputes, contributing an integrated approach to the analysis of water conflicts, by providing technical solutions combined with an in-depth analysis of social dynamics. The analysis focuses on an ongoing water conflict in El Carracillo region (Spain), related to an artificial aquifer recharge project. This case study involves two competing water users: on the one hand horticultural farmers; and, on the other hand, ecosystem services provided by Cega river, from which water is diverted in order to recharge the aquifer. Based on a stakeholder analysis, a tool was built to support participatory processes by facilitating mediation procedures. The optimization showed that solutions exist that account for ecosystem needs without causing major negative impacts on El Carracillo agriculture, and suggested that a re-negotiation of the rules that govern water diversion from Cega river is needed.

Optimization of time and cost in construction projects has been subject to extensive research since the development of the Critical Path Method (CPM). Many researchers have investigated various versions of the well-known Time-Cost Trade-off (TCT) problem including linear, convex, concave, and also the discrete (DTCT) version. Traditional methods in the literature for optimizing time and cost of construction projects range from mathematical methods to evolutionary-based ones, such as genetic algorithms, particle swarm, ant-colony, and leap frog optimization. However, none of the existing research studies has dealt with the optimization of large-scale projects in which any small saving would be significant. Traditional approaches have all been applied to projects of less than 100 activities which are far less than what exists in real-world construction projects. The objective of this study is to utilize recent developments in computation technology and novel optimization techniques such as Constraint Programming (CP) to improve the current limitations in solving large-scale DTCT problems. Throughout the first part of this research, an Excel-based TCT model has been developed to investigate the performance of traditional optimization methods, such as mathematical programming and genetic algorithms, for solving large TCT problems. The result of several experimentations confirms the inefficiency of traditional methods for optimizing large TCT problems. Subsequently, a TCT model has been developed using Optimization Programming Language (OPL) to implement the Constraint Programming (CP) technique. CP Optimizer of IBM ILOG Optimization Studio has been used to solve the model and to successfully optimize several projects ranging from a small project of 18 activities to very large projects consisting of more than 10,000 activities. Constraint programming proved to be very efficient in solving large-scale TCT problems, generating substantially better results in terms of solution quality and processing speed. While traditional optimization methods have been used to optimize projects consisting of less than one hundred activities, constraint programming demonstrated its capability of solving TCT problems comprising of thousands of activities. As such, the developed model represents a significant improvement in optimization of time and cost of large-scale construction projects and can greatly enhance the level of planning and control in such projects.

博士
國立成功大學
電機工程學系碩博士班
94
In a high-performance superscalar processor, the dynamic instruction scheduler often comes with poor scalability and high complexity due to the expensive instruction wakeup operation. This thesis presents three optimizations for wakeup logic to improve the power consumption, wakeup latency, area cost, and scalability. First, a wakeup design that pre-decodes the source tag is proposed. This design removes the reads of the destination tag and eliminates the redundant tag matches by matching the source tag directly with only the selected grant line. Next, the second design exploits the wakeup locality that most of the wakeup distances between two dependent instructions are short. By limiting the wakeup operation within a small wakeup range, the load capacitance and circuit activities can be alleviated. Third, a scheduling technique is proposed to schedule instructions into the segmented issue window based on their wakeup addresses. During wakeup process, the wakeup operation is only performed in the segment selected by the wakeup address of the result tag. The experimental results show that the proposed designs save the power consumption, and reduce the wakeup latency compared to the conventional designs. The results also show that the proposed designs have excellent scalability.