Дисертації з теми "Quadratically Constrained Linear Programming"
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P, Van Voorhis Timothy. "The quadratically constrained quadratic program." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/23379.
Повний текст джерелаWang, Guanglei. "Relaxations in mixed-integer quadratically constrained programming and robust programming." Thesis, Evry, Institut national des télécommunications, 2016. http://www.theses.fr/2016TELE0026/document.
Повний текст джерелаMany real life problems are characterized by making decisions with current information to achieve certain objectives. Mathematical programming has been developed as a successful tool to model and solve a wide range of such problems. However, many seemingly easy problems remain challenging. And some easy problems such as linear programs can be difficult in the face of uncertainty. Motivated by a telecommunication problem where assignment decisions have to be made such that the cloud virtual machines are assigned to servers in a minimum-cost way, we employ several mathematical programming tools to solve the problem efficiently and develop new tools for general theoretical problems. In brief, our work can be summarized as follows. We provide an exact formulation and several reformulations on the cloud virtual machine assignment problem. Then several valid inequalities are used to strengthen the exact formulation, thereby accelerating the solution procedure significantly. In addition, an effective Lagrangian decomposition is proposed. We show that, the bounds providedby the proposed Lagrangian decomposition is strong, both theoretically and numerically. Finally, a symmetry-induced model is proposed which may reduce a large number of bilinear terms in some special cases. Motivated by the virtual machine assignment problem, we also investigate a couple of general methods on the approximation of convex and concave envelopes for bilinear optimization over a hypercube. We establish several theoretical connections between different techniques and prove the equivalence of two seeming different relaxed formulations. An interesting research direction is also discussed. To address issues of uncertainty, a novel paradigm on general linear problems with uncertain parameters are proposed. This paradigm, termed as multipolar robust optimization, generalizes notions of static robustness, affinely adjustable robustness, fully adjustable robustness and fills the gaps in-between. As consequences of this new paradigms, several known results are implied. Further, we prove that the multipolar approach can generate a sequence of upper bounds and a sequence of lower bounds at the same time and both sequences converge to the robust value of fully adjustable robust counterpart under some mild assumptions
Crowe, Mitch. "Nonlinearly constrained optimization via sequential regularized linear programming." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/29648.
Повний текст джерелаZhao, Jianmin. "Optimal Clustering: Genetic Constrained K-Means and Linear Programming Algorithms." VCU Scholars Compass, 2006. http://hdl.handle.net/10156/1583.
Повний текст джерелаHardin, Jill Renea. "Resource-constrained scheduling and production planning : linear programming-based studies." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/24857.
Повний текст джерелаWang, Yanhui. "Affine scaling algorithms for linear programs and linearly constrained convex and concave programs." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/24919.
Повний текст джерелаViana, Luiz Alberto do Carmo. "Dependency constrained minimum spanning tree." Universidade Federal do CearÃ, 2016. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=17302.
Повний текст джерелаIntroduzimos o problema de Ãrvore Geradora com DependÃncias MÃnima, AGDM(G,D,w), definido sobre um grafo G(V,E) e um digrafo D(E,A), cujos vÃrtices sÃo as arestas de G e cujos arcos definem dependÃncias entre tais arestas. O problema consiste em encontrar, dentre as Ãrvores geradoras do grafo G(V,E) que satisfaÃam as restriÃÃes de dependÃncia impostas pelo digrafo de entrada D(E,A), uma que tenha custo mÃnimo, segundo a ponderaÃÃo w das arestas de G. As restriÃÃes de dependÃncia exigem que uma aresta e de G sà pode fazer parte de uma soluÃÃo se for uma fonte em D ou se fizer parte da soluÃÃo alguma outra aresta à tal que o arco (e′, e) esteja em D. Provamos que decidir se hà soluÃÃo viÃvel para AGDM(G,D,w) à um problema NP-completo, mesmo quando G à um cacto cordal e D à a uniÃo de arborescÃncias de altura no mÃximo 2. Sua NP-completude tambÃm à mostrada ainda que G seja bipartido, as restriÃÃes de dependÃncia ocorram apenas entre arestas adjacentes de G e formem arborescÃncias de altura no mÃximo 2. Resultados idÃnticos sÃo obtidos para as variantes do problema onde, nas restriÃÃes de dependÃncia, substitui-se o requisito âalgumaâ por âexatamente umaâ ou âtodaâ. Para resolver o problema, apresentamos algumas formulaÃÃes de programaÃÃo inteira e desigualdades vÃlidas. Propomos uma estratÃgia para reduzir a dimensÃo do problema, excluindo arestas de G com base na estrutura de D. Avaliamos os modelos e algoritmos propostos usando instÃncias geradas aleatoriamente. Resultados computacionais sÃo reportados.
We introduce the Dependency Constrained Minimum Spanning Tree Problem, DCMST(G,D,w), defined over a graph G(V,E) and a digraph D(E,A), whose vertices are the edges of G and whose arcs describe dependency relations between these edges. Such problem consists of finding, among the spanning trees of G(V,E) satisfying the dependency constraints imposed by D(E,A), that one whose cost is minimum, according to a edgeweight function w. The dependency constraints impose that an edge e of G can be part of a solution either if it is a source in D or if some other edge e′, such that the arc (e′, e) is in D, is part of it as well. We prove that deciding whether there is a feasible solution to DCMST(G,D,w) is an NP-complete problem, even if G is a chordal cactus and D is a union of arborescences of height at most 2. NP-completeness also applies if G is bipartite, the dependency constraints occur only between adjacent edges of G and their related arcs describe arborescences whose height is at most 2. The same results are obtained for the problem variants which demand that, instead of âsomeâ, âexactly oneâor âallâdependencies be part of a solution. To solve the problem, we introduce some integer programming formulations and some valid inequalities. We propose a strategy to reduce the problem dimension by excluding some edges of G according to the structure of D. We evaluate the introduced models and algorithms using randomly generated instances. Computational results are reported.
Aslan, Murat. "The Cardinality Constrained Multiple Knapsack Problem." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12610131/index.pdf.
Повний текст джерелаPedroso, Lucas Garcia. "Programação não linear sem derivadas." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307473.
Повний текст джерелаTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
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Resumo: Neste trabalho propomos um algoritmo Lagrangiano Aumentado sem derivadas para o problema geral de otimização. Consideramos o método introduzido por Andreani, Birgin, Martínez e Schuverdt, eliminando os cálculos de derivadas inerentes ao algoritmo através de modificações adequadas no critério de parada. Foram mantidos os bons resultados teóricos do método, como convergência sob a condição de qualificação CPLD e a limitação do parâmetro de penalidade. Experimentos numéricos são apresentados, entre os quais destacamos um exemplo de problema sem derivadas baseado na simulação de áreas de figuras no plano.
Abstract: We propose in this work a derivative-free Augmented Lagrangian algorithm for the general problem of optimization. We consider the method due to Andreani, Birgin, Martínez and Schuverdt, eliminating the derivative computations in the algorithm by making suitable modifications on the stopping criterion. The good theoretical results of the method were mantained, as convergence under the CPLD constraint qualification and the limitation of the penalty parameter. Numerical experiments are presented, and the most relevant of them is an example of derivative-free problem based on the simulation of areas of figures on the plane.
Doutorado
Otimização Matematica
Doutor em Matemática Aplicada
Vanden, Berghen Frank. "Constrained, non-linear, derivative-free, parallel optimization of continuous, high computing load, noisy objective functions." Doctoral thesis, Universite Libre de Bruxelles, 2004. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211177.
Повний текст джерелаDoctorat en sciences appliquées
info:eu-repo/semantics/nonPublished
Lieder, Felix [Verfasser]. "Projection Based Methods for Conic Linear Programming — Optimal First Order Complexities and Norm Constrained Quasi Newton Methods / Felix Lieder." Düsseldorf : Universitäts- und Landesbibliothek der Heinrich-Heine-Universität Düsseldorf, 2018. http://d-nb.info/1166398277/34.
Повний текст джерелаNguyen, Ngoc Anh. "Explicit robust constrained control for linear systems : analysis, implementation and design based on optimization." Thesis, Université Paris-Saclay (ComUE), 2015. http://www.theses.fr/2015SACLC012/document.
Повний текст джерелаPiecewise affine (PWA) feedback control laws have received significant attention due to their relevance for the control of constrained systems, hybrid systems; equally for the approximation of nonlinear control. However, they are associated with serious implementation issues. Motivated from the interest in this class of particular controllers, this thesis is mostly related to their analysis and design.The first part of this thesis aims to compute the robustness and fragility margins for a given PWA control law and a linear discrete-time system. More precisely, the robustness margin is defined as the set of linear time-varying systems such that the given PWA control law keeps the trajectories inside a given feasible set. On a different perspective, the fragility margin contains all the admissible variations of the control law coefficients such that the positive invariance of the given feasible set is still guaranteed. It will be shown that if the given feasible set is a polytope, then so are these robustness/fragility margins.The second part of this thesis focuses on inverse optimality problem for the class of PWA controllers. Namely, the goal is to construct an optimization problem whose optimal solution is equivalent to the given PWA function. The methodology is based on emph convex lifting: an auxiliary 1− dimensional variable which enhances the convexity characterization into recovered optimization problem. Accordingly, if the given PWA function is continuous, the optimal solution to this reconstructed optimization problem will be shown to be unique. Otherwise, if the continuity of this given PWA function is not fulfilled, this function will be shown to be one optimal solution to the recovered problem.In view of applications in linear model predictive control (MPC), it will be shown that any continuous PWA control law can be obtained by a linear MPC problem with the prediction horizon at most equal to 2 prediction steps. Aside from the theoretical meaning, this result can also be of help to facilitate implementation of PWA control laws by avoiding storing state space partition. Another utility of convex liftings will be shown in the last part of this thesis to be a control Lyapunov function. Accordingly, this convex lifting will be deployed in the so-called robust control design based on convex liftings for linear system affected by bounded additive disturbances and polytopic uncertainties. Both implicit and explicit controllers can be obtained. This method can also guarantee the recursive feasibility and robust stability. However, this control Lyapunov function is only defined over the maximal λ −contractive set for a given 0 ≤ λ < 1 which is known to be smaller than the maximal controllable set. Therefore, an extension of the above method to the N-steps controllable set will be presented. This method is based on a cascade of convex liftings where an auxiliary variable will be used to emulate a Lyapunov function. Namely, this variable will be shown to be non-negative, to strictly decrease for N first steps and to stay at 0 afterwards. Accordingly, robust stability is sought
Siqueira, Abel Soares 1986. "Controle dinâmico de infactibilidade para programação não linear." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307118.
Повний текст джерелаTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: Uma maneira de resolver problemas gerais de programação não linear é utilizar estratégias de passos compostos. Essas estratégias normalmente combinam um passo tangente às restrições e um passo normal, alternando entre a diminuição da função objetivo e da norma da infactibilidade. Esse tipo de método exige o controle dos passos ou dos iterandos, para que não se perca o progresso de um vii passo no outro. Apresentaremos uma extensão do método de Controle Dinâmico da Infactibilidade, que utiliza uma estratégia de controle de passos chamado de Cilindros de Confiança. Esse método foi desenvolvido para problemas com restrições apenas de igualdade, e nossa extensão lida com restrições gerais. Mostraremos testes numéricos comparando nosso método com um método do mesmo tipo
Abstract: One way to solve general nonlinear programming problems is the composite-step strategies. These strategies usually combine a step tangent to the constraints and a normal step, alternating between reducing the objective function value and the norm of the infeasibility. This kind of method requires the control of the steps or the iterates, in order to prevent one step from destroying the progress of another. We will present an extension of the Dynamic Control of Infeasibility method, which utilizes a strategy to control the steps known as Trust Cylinders. This method was originally designed for problems with equality contraints only, and our extension will handle general constraints. We'll show numerical experiments comparing our method with another composite-step method
Doutorado
Matematica Aplicada
Doutor em Matemática Aplicada
Mitradjieva-Daneva, Maria. "Feasible Direction Methods for Constrained Nonlinear Optimization : Suggestions for Improvements." Doctoral thesis, Linköping : Department of Mathematics, Linköping University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8811.
Повний текст джерелаQiu, Feng. "Probabilistic covering problems." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47567.
Повний текст джерелаSahin, Cem. "Optimization Of Electricity Markets In The Price Based And Security Constrained Unit Commitment Problems Frameworks." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612242/index.pdf.
Повний текст джерела&bull
A discrete demand response model to consider active participation of the consumers, &bull
A hybrid deterministic/stochastic contingency model to represent the N-1 contingencies together with the uncertainties related with the wind power generation and system load. It is observed that the curtailment of available wind power capacity would enable the TSO to take corrective actions against occurrence of the contingencies and realization of the uncertainties in the most possible economical manner.
Excoffier, Mathilde. "Chance-Constrained Programming Approaches for Staffing and Shift-Scheduling Problems with Uncertain Forecasts : application to Call Centers." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112244/document.
Повний текст джерелаThe staffing and shift-scheduling problems in call centers consist in deciding how many agents handling the calls should be assigned to work during a given period in order to reach the required Quality of Service and minimize the costs. These problems are subject to a growing interest, both for their interesting theoritical formulation and their possible applicative effects. This thesis aims at proposing chance-constrained approaches considering uncertainty on demand forecasts.First, this thesis proposes a model solving the problems in one step through a joint chance-constrained stochastic program, providing a cost-reducing solution. A continuous-based approach leading to an easily-tractable optimization program is formulated with random variables following continuous distributions, a new continuous relation between arrival rates and theoritical real agent numbers and constraint linearizations. The global risk level is dynamically shared among the periods during the optimization process, providing reduced-cost solution. The resulting solutions respect the targeted risk level while reducing the cost compared to other approaches.Moreover, this model is extended so that it provides a better representation of real situations. First, the queuing system model is improved and consider the limited patience of customers. Second, another formulation of uncertainty is proposed so that the period correlation is considered.Finally, another uncertainty representation is proposed. The distributionally robust approach provides a formulation while assuming that the correct probability distribution is unknown and belongs to a set of possible distributions defined by given mean and variance. The problem is formulated with a joint chance constraint. The risk at each period is a decision variable to be optimized. A deterministic equivalent problem is proposed. An easily-tractable mixed-integer linear formulation is obtained through piecewise linearizations
Cheon, Myun-Seok. "Global Optimization of Monotonic Programs: Applications in Polynomial and Stochastic Programming." Diss., Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-04152005-130317/unrestricted/Cheon%5FMyunSeok%5F200505%5Fphd.pdf.
Повний текст джерелаBarnes, Earl, Committee Member ; Shapiro, Alex, Committee Member ; Realff, Matthew, Committee Member ; Al-Khayyal, Faiz, Committee Chair ; Ahmed, Shabbir, Committee Co-Chair. Includes bibliographical references.
Grose, Roger T. "Cost-constrained project scheduling with task durations and costs that may increase over time demonstrated with the U.S. Army future combat systems /." Thesis, View thesis via NPS View thesis via DTIC, 2004. http://handle.dtic.mil/100.2/ADA424957.
Повний текст джерелаTitle from title screen (viewed June 28, 2005). "June 2004." Includes bibliographical references (p. 59-61). Also issued in paper format.
Grey, Audley Bruce. "Unified solution of security-constrained unit commitment (SCUC) problem using a linear programming methodology : a dissertation presented to the faculty of the Graduate School, Tennessee Technological University /." Click to access online version, 2007. http://proquest.umi.com/pqdweb?index=88&did=1397913351&SrchMode=1&sid=1&Fmt=6&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1255446163&clientId=28564.
Повний текст джерелаPrudente, Leandro da Fonseca 1985. "Inviabilidade em métodos de lagrangiano aumentado." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307467.
Повний текст джерелаTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: Algoritmos de programação não-linear práticos podem convergir para pontos inviáveis mesmo quando o problema a ser resolvido é viável. Quando isso ocorre, é natural que o usuário mude o ponto inicial e/ou parâmetros algorítmicos e reaplique o método na tentativa de encontrar uma solução viável e ótima. Desta forma, o ideal é que um algoritmo não só seja eficiente em encontrar soluções viáveis, mas também que detecte rapidamente quando ele está fadado a convergir para um ponto inviável. Na tentativa de atingir esse objetivo, apresentamos modificações em um algoritmo baseado em Lagrangiano aumentado de modo que, no caso de convergência para um ponto inviável, os subproblemas são resolvidos com tolerâncias moderadas e, mesmo assim, as propriedades de convergência global são mantidas. Experimentos numéricos são apresentados
Abstract Practical Nonlinear Programming algorithms may converge to infeasible points even when the problem to be solved is feasible. When this occurs, it is natural for the user to change the starting point and/or algorithmic parameters and reapply the method in an attempt to find a feasible and optimal solution. Thus, the ideal is that an algorithm is eficient not only in finding feasible solutions, but also in quickly detecting when it is fated to converge to an infeasible point. In pursuit of this goal, we present modifications of an algorithm based on Augmented Lagrangians so that, in the case of convergence to an infeasible point, the subproblems are solved with moderate tolerances and, even then, the global convergence properties are maintained. Numerical experiments are presented
Doutorado
Matematica Aplicada
Doutor em Matemática Aplicada
Oliveira, Fabiana Rodrigues de. "Estudo de alguns métodos clássicos de otimização restrita não linear." Universidade Federal de Uberlândia, 2012. https://repositorio.ufu.br/handle/123456789/16795.
Повний текст джерелаIn this work some classical methods for constrained nonlinear optimization are studied. The mathematical formulations for the optimization problem with equality and inequality constrained, convergence properties and algorithms are presented. Furthermore, optimality conditions of rst order (Karush-Kuhn-Tucker conditions) and of second order. These conditions are essential for the demonstration of many results. Among the methods studied, some techniques transform the original problem into an unconstrained problem (Penalty Methods, Augmented Lagrange Multipliers Method). In others methods, the original problem is modeled as one or as a sequence of quadratic subproblems subject to linear constraints (Quadratic Programming Method, Sequential Quadratic Programming Method). In order to illustrate and compare the performance of the methods studied, two nonlinear optimization problems are considered: a bi-dimensional problem and a problem of mass minimization of a coil spring. The obtained results are analyzed and confronted with each other.
Neste trabalho são estudados alguns métodos clássicos de otimização restrita não linear. São abordadas a formulação matemática para o problema de otimização com restrições de igualdade e desigualdade, propriedades de convergência e algoritmos. Além disso, são relatadas as condições de otimalidade de primeira ordem (condições de Karush-Kuhn-Tucker) e de segunda ordem. Estas condições são essenciais para a demonstração de muitos resultados. Dentre os métodos estudados, algumas técnicas transformam o problema original em um problema irrestrito (Métodos de Penalidade, Método dos Multiplicadores de Lagrange Aumentado). Em outros métodos, o problema original é modelado como um ou uma seqüência de subproblemas quadráticos sujeito _a restrições lineares (Método de Programação Quadrática, Método de Programação Quadrática Seqüencial). A fim de ilustrar e comparar o desempenho dos métodos estudados são considerados dois problemas de otimização não linear: um problema bidimensional e o problema de minimização da massa de uma mola helicoidal. Os resultados obtidos são examinados e confrontados entre si.
Mestre em Matemática
Gentil, Jan Marcel Paiva. "Estudo e implementação de um método de restrições ativas para problemas de otimização em caixas." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-28082010-115947/.
Повний текст джерелаBox-constrained optimization problems are of great importance not only for naturally arising in several real-life problems formulation, but also for their occurrence as sub-problems in both penalty and Augmented Lagrangian methods for solving nonlinear programming problems. This work aimed at studying a recently introduced active-set method for box-constrained optimization called ASA and comparing it to the latest version of GENCAN, which is also an active-set method. For that purpose, we designed a robust and thorough testing methodology intended to remedy many of the widely criticized aspects of prior works. Thereby, we could draw conclusions leading to GENCAN\'s further development, as it later became evident by means of the same methodology herein proposed.
Bueno, Luís Felipe Cesar da Rocha 1983. "Otimização com restrições LOVO, restauração inexata e o equilíbrio inverso de Nash." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307465.
Повний текст джерелаTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica.
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Resumo: Nesse trabalho serão propostos métodos de Lagrangiano Aumentado para tratar problemas com restrições do tipo LOVO, serão propostos novos métodos de Restauração Inexata e será introduzido o conceito de Equilíbrio Inverso de Nash. Teoremas sobre condições de otimalidade para problemas do tipo LOVO serão apresentados. Um algoritmo do tipo Lagrangiano Aumentado será proposto para abordar esse problema e teoremas de convergência global serão demonstrados. Resultados computacionais serão realizados para uma aplicação em otimização de carteiras em investimentos de grande impacto. Um método híbrido de Restauração Inexata será proposto combinando uma modificação, que usa o Lagrangiano Afiado como função de mérito, do método global de Fischer e Friedlander e o método local de Birgin e Martínez. Teoremas de convergência global e local serão apresentados. Um método de Restauração Inexata para problemas em que as derivadas da função objetivo não estejam disponíveis será introduzido. Nesse método todas as ferramentas da otimização tradicional serão usadas na fase de restauração e uma regularização será feita na fase de otimização. Teoremas de convergência global serão demonstrados e resultados numéricos apresentados. O conceito de Equilíbrio Inverso de Nash será introduzido e um método de Restauração Inexata será proposto para abordar esse problema. Esse método será uma extensão de um novo método de Restauração Inexata para problemas em dois níveis que também será proposto neste trabalho. Exemplos ilustrativos para uma aplicação para o problema de equilíbrio de Arrow-Debreu serão exibidos
Abstract: In this work an Augmented Lagrangian method will be proposed to deal with LOVO constraints, also some new Inexact Restoration methods will be presented and the Inverse Nash Equilibrium concept will be introduced. Theorems about optimality conditions for LOVO-like problems will be presented. Three Augmented Lagrangian algorithms will be proposed to approach this problem and global convergence theorems will be proved. Computational results will be performed for an application in portfolio optimization with impact. A modification of the Fischer-Friedlander global method using the Sharp Lagrangian as a merit function will be proposed. A hybrid Inexact Restoration method combining this modification and the Birgin-Martínez local method will be introduced. Global and local convergence theorems will be presented. An Inexact Restoration method for problems in which the derivatives of the objective function are not available will be introduced. In this method it will be used all the optimization traditional tools in the restoration process as well as a regularization strategy in the optimization phase. Global convergence theorems will be demonstrated and numerical results will be presented. The concept of Inverse Nash Equilibrium will be introduced and an Inexact Restoration method will be proposed to deal with this problem. This method is an extension of a new Inexact Restoration method for bilevel programming that will also be proposed in this work. Some illustrative examples for an application for the Arrow- Debreu equilibrium problem will be given
Doutorado
Matematica Aplicada
Doutor em Matemática Aplicada
Sobral, Francisco Nogueira Calmon 1984. "Otimização sem derivadas em conjuntos magros." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307469.
Повний текст джерелаTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: Os problemas de otimização sem derivadas surgem de modelos para os quais as derivadas das funções e das restrições envolvidas, por alguma razão, não estão disponíveis. Os motivos variam desde usuários que não querem programar as derivadas até funções excessivamente complexas e caixas-pretas, oriundas de simulações só possíveis graças ao crescimento na capacidade de processamento dos computadores. Acompanhando esse crescimento, o número de algoritmos para resolver problemas de otimização sem derivadas aumentou nos últimos anos. Porém, poucos são aqueles que conseguem lidar de forma eficiente com problemas cujos domínios são magros, como, por exemplo, quando há restrições de igualdade. Neste trabalho, apresentamos a teoria e implementação de dois algoritmos capazes de trabalhar com domínios magros em problemas de otimização sem derivadas. Ambos partem da premissa de que a parte mais custosa na resolução é a avaliação da função objetivo. Com isso em mente, o processo de resolução é dividido em duas fases. Na fase de restauração, buscamos por pontos menos inviáveis sem utilizar avaliações da função objetivo. Na fase de minimização, ou otimização, o objetivo é reduzir a função objetivo com o uso de algoritmos bem estabelecidos para problemas sem derivadas com restrições simples. O primeiro algoritmo utiliza ideias de Restauração Inexata associadas a uma tolerância decrescente à inviabilidade. Utilizando hipóteses simples e usuais dos métodos de busca direta direcional, mostramos propriedades de convergência a minimizadores globais. O segundo algoritmo recupera totalmente os resultados teóricos de um algoritmo recente de Restauração Inexata com busca linear e aplica-se a problemas nos quais apenas as derivadas da função objetivo não estão disponíveis. Testes numéricos mostram as boas propriedades dos dois algoritmos, em particular quando comparados com algoritmos baseados em penalidades
Abstract: Derivative-free optimization problems arise from models whose derivatives of some functions are not available. This information is unavailable due to extremely complex and black-box functions, originated from simulation procedures, or even to user inability. Following the growth in the number of applications, the number of derivative-free algorithms has increased in the last years. However, few algorithms are able to handle thin feasible domains efficiently, for example, in the presence of equality nonlinear constraints. In the present work, we describe the theory and implementation of two algorithms capable of dealing with thin-constrained derivative-free problems. Their definition considers that the objective function evaluation is the most expensive part of the problem. Based on this principle, the process of solving a problem is split into two phases. In the restoration phase, we try to improve the feasibility without evaluating the objective function. In the minimization phase, the aim is to decrease the objective function value by using well-established algorithms in order to solve derivative-free problems with simple constraints. The _rst algorithm uses Inexact Restoration ideas together with a decreasing infeasibility tolerance. Under the usual hypotheses of direct search methods, we show global minimization results. The second algorithm extends to the derivative-free case all the theoretical results obtained in a recent line-search Inexact Restoration algorithm. In this approach, only the derivatives of the objective function are not available. We perform numerical experiments to show the advantages of each algorithm, in particular when comparing with penalty-like algorithms
Doutorado
Matematica Aplicada
Doutor em Matemática Aplicada
Dutia, Dharini. "Multi-Robot Task Allocation and Scheduling with Spatio-Temporal and Energy Constraints." Digital WPI, 2019. https://digitalcommons.wpi.edu/etd-theses/1298.
Повний текст джерелаParis, Jean-Marc. "Validation de données de systèmes dynamiques non-linéaires : application à la détection de défauts." Vandoeuvre-les-Nancy, INPL, 1998. http://www.theses.fr/1998INPL048N.
Повний текст джерелаCanahuire, Cabello Ruth Vanessa 1983. "Projeto de controladores H-infinito de ordem reduzida e compensação de saturação em estruturas flexíveis." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/265939.
Повний текст джерелаTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica
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Resumo: A síntese de controle H-infinito de estruturas flexíveis pode levar à obtenção de controladores de alta ordem. Estes controladores podem apresentar dificuldades para a implementação prática acarretando atrasos de resposta no sistema. Para evitar esse problema, este trabalho apresenta duas sínteses de controladores H-infinito de ordem reduzida por realimentação de saída. Para este propósito, são formulados dois problemas de otimização para a obtenção de controladores de ordem reduzida considerando que as matrizes de estado do controlador estão na forma canônica controlável e canônica modal. As duas sínteses propostas estão baseadas na minimização da norma H-infinito garantindo a estabilidade do sistema em malha fechada. Outro problema considerado neste trabalho são os efeitos de saturação dos atuadores sobre o sistema controlado. A saturação, quando presente no sistema, pode levar a uma perda de desempenho e as vezes à instabilidade da planta. Para tratar o problema de saturação é proposto um problema de otimização baseado no projeto de compensadores anti-windup. A abordagem proposta usa a síntese do problema H-infinito para minimizar diretamente os efeitos do sinal de saturação sobre o sinal de desempenho. Finalmente, as formulações são verificadas no controle ativo de vibração sobre um modelo teórico e em uma bancada experimental com uma viga de alumínio engastada-livre. Os métodos mostraram ter bom desempenho garantindo a estabilidade do sistema em malha fechada. Os problemas de otimização são resolvidos usando algoritmos genéticos e alguns aspectos numéricos são discutidos
Abstract: The H-infinity controller synthesis for flexible structures leads to full-order controllers. This can represent difficulties for practical controller implementation arising delay in the system response. To avoid this difficulty, this work presents two reduced order H-infinity controllers synthesis based on output feedback. For this goal, it is formulated two optimization problem to obtain a reduced order controller in its state-space controllable canonical form and state-space modal canonical form. The two proposed synthesis are based on the minimization of the H-infinity norm ensuring the stability of the closed loop system. Another problem considered in this work is related to the effects of saturation of the actuators on the controlled system. The saturation in the system can lead to a performance loss and occasionally to the instability of the plant. An optimization problem based on anti-windup compensator design is proposed to treat this problem. The proposed approach uses the H-infinity controller synthesis to minimize directly the saturation effects on the performance signal. Finally, the formulations are verified in the active control of vibration of a theoretical model and a cantilever aluminium beam is used on an experimental bench. The methods proposed presented good performance in terms of the stability of the closed loop system. The optimization problems are solved using genetic algorithms and some numerical aspects are discussed
Doutorado
Mecanica dos Sólidos e Projeto Mecanico
Doutora em Engenharia Mecânica
Sahli, Abderrahim. "Problèmes d'ordonnancement avec production et consommation des ressources." Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2309/document.
Повний текст джерелаThis thesis investigates the Extended Resource Constrained Project Scheduling Problem (ERCPSP). ERCPSP is a general scheduling problem where the availability of a resource is depleted and replenished at the occurrence times of a set of events. It is an extension of the Resource Constrained Project Scheduling Problem (RCPSP) where activities are replaced by events, which have to be scheduled subject to generalized precedence relations. We are interested in this thesis in proposing new methodologies and approaches to solve ERCPSP. First, we study some polynomial cases of this problem and we propose a dynamic programming algorithm to solve the parallel chain case. Then, we propose lower bounds, mixed integer programming models, and a branch-and-bound method to solve ERCPSP. Finally, we develop an instance generator dedicated to this problem
Wang, Chenghao. "Contribution à l’optimisation robuste de réseaux." Thesis, Compiègne, 2021. http://www.theses.fr/2021COMP2632.
Повний текст джерелаThis Ph.D. Thesis is focused on proposing new optimization modeling and algorithmic approaches for dealing with real-world network optimization problems arising in the transportation and telecommunications fields. Since the focus has been on real-world applications, a relevant aspect that has been taken into account is data uncertainty, i.e. the fact that the value of a subset of input data of the problem is not exactly known when the problem is solved. More precisely, in the context of transportation problems, it was considered the flight level assignment problem, which arises in air traffic management. It aims at establishing the flight levels of a set of aircraft in order to improve the total assignment revenue, to reduce the total number of flight conflicts and also the total en-route delay. In this context, we proposed a new chance-constrained optimization problem and iterative constraint-generation heuristic which is based on both analytical and sampling methods. Besides transportation problems, this Thesis has also focused on the optimal design of 5th generation of wireless networks (5G) considering Superfluid and virtual architectures. Specifically, the 5G Superfluid architecture is based on atomic virtual entities called Reusable Functional Block (RFB). We investigated the problem of minimizing the total installation costs of a 5G Superfluid network (composed of virtual entities and realized over a physical network) while guaranteeing constraint on user coverage, downlink traffic performance and technical constraints on RFBs of different nature. To solve this hard problem, we proposed a Benders decomposition approach. Concerning instead the design of general virtual networks, we adopted a green paradigm that pursues energy-efficiency and tackled a state-of-the-art robust mixed integer linear programming formulation of the problem, by means of a new matheuris tic based on combining a genetic algorithm with exact large neighborhood searches. Results of computational tests executed considering realistic problem instances have shown the validity of all the new optimization modeling and algorithmic approaches proposed in this Thesis for the transportation and telecommunications problems sketched above
Andretta, Marina. "Tópicos em otimização com restrições lineares." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-01092008-114422/.
Повний текст джерелаAugmented Lagrangian methods are widely used to solve general nonlinear programming problems. In these methods, one can split the set of constraints in two groups: the set of easy and hard constraints. A constraint is called easy if there is an efficient method available to solve problems subject to that kind of constraint. Otherwise, the constraints are called hard. Augmented Lagrangian methods solve, at each iteration, problems subject to the set of easy constraints while penalizing the set of hard constraints. Linearly constrained problems appear frequently, sometimes as a result of a linear approximation of a problem, sometimes as an augmented Lagrangian subproblem. Therefore, an efficient method to solve linearly constrained problems is important for the implementation of efficient methods to solve nonlinear programming problems. In this thesis, we begin by considering box constraints as the set of easy constraints. We introduce a version of BETRA to solve large scale problems. BETRA is an active-set method that uses a trust-region strategy to work within the faces and spectral projected gradient to leave the faces. To solve each iteration\'s subproblem of ALGENCAN (an augmented Lagrangian method) we use either the dense or the sparse version of BETRA. We develope rules to decide which box-constrained inner solver should be used at each augmented Lagrangian iteration that considers the main characteristics of the problem to be solved. Then, we introduce two active-set methods to solve linearly constrained problems (BETRALIN and GENLIN). These methods use Partial Spectral Projected Gradient method to change the active set of constraints. The Partial Spectral Projected Gradient method was developed specially for this purpose. It computes projections onto a subset of the linear constraints, aiming to make the projections more efficient. At last, having introduced a linearly-constrained solver, we consider the set of linear constraints as the set of easy constraints. We use BETRALIN and GENLIN in the framework of augmented Lagrangian methods and verify, using numerical experiments, the efficiency and robustness of those methods that work with linear constraints and penalize the nonlinear constraints.
López, Ramos Francisco. "Conjoint design of railway lines and frequency setting under semi-congested scenarios." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/144940.
Повний текст джерелаGiuliani, Luca. "Extending the Moving Targets Method for Injecting Constraints in Machine Learning." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23885/.
Повний текст джерелаFoster, James Daniel. "Mixed-integer quadratically-constrained programming, piecewise-linear approximation and error analysis with applications in power flow." Thesis, 2014. http://hdl.handle.net/1959.13/1048192.
Повний текст джерелаThis thesis investigates of the structure and solution of quadratically constrained optimization problems incorporating models of electrical power flow through transmission networks. Approximation of the equations and inequalities describing electrical power flow play a central role. Mixed-integer nonlinear programming (MINLP) theory is applied to determining good bounds to the optimal values of power flow optimization problems. After reviewing the literature on power system planning and design methods using mixed-integer programming, we apply recently developed MINLP software tools to the problem of distributed generation design in a distribution network. We investigate the merits of three mixed-integer programming approaches for finding good designs for new generator installation, along with a method for determining lower bounds on the optimal design objective by solving a knapsack problem. We then turn our attention to a typical continuous optimization problem with power flow constraints with the objective of minimising power loss. The natural question is how to construct good approximations of the equations and inequalities describing power flow. The analytic derivation of the error in the solutions of an approximate system of equations is considered. We then give a united analysis of the special structure of certain nonconvex quadratic functions that appear within the power flow constraints. It is seen that these quadratic functions can be reduced to the symmetric paraboloid function over the real plane by a linear eigenvector-based transformation of variables. Techniques are then presented for exploiting this special paraboloid structure. A systematic study of piecewise-linear approximations to this fundamental paraboloid function is set forth through the framework of the Delaunay triangulation, an object possessing a rich theory from the area of computational geometry. We consider piecewise-linear functions which interpolate the paraboloid function at the vertices of partitions of convex regions, and propose a theory for the optimization of partition geometry. Such partition optimization is over families of partitions possessing the same topology and a fixed number of polytopes, with the objective that an optimal partition minimises the maximum separation between the paraboloid function and the piecewise-linear function generated from the partition. We finally present a novel global optimization approach to forming strong outer approximating convex programs of nonconvex power flow optimization problems. This is achieved through replacing reverse convex quadratic inequality constraints in the transformed problem with a linear mixed-integer model based on piecewise-linear functions interpolating the paraboloid function. Our approach enables the computation of lower bounds to the value of the global optimum of power flow optimization problems with convex objectives.
Ding, Yichuan. "On Efficient Semidefinite Relaxations for Quadratically Constrained Quadratic Programming." Thesis, 2007. http://hdl.handle.net/10012/3044.
Повний текст джерела"Novel Reformulations and Relaxations for Quadratically Constrained Quadratic Programming." 2016. http://repository.lib.cuhk.edu.hk/en/item/cuhk-1292666.
Повний текст джерела"Approximation algorithms for Lp-ball and quadratically constrained polynomial optimization problems." 2013. http://library.cuhk.edu.hk/record=b6115682.
Повний текст джерелаIn this thesis, we present polynomial time approximation algorithms for solving various homogeneous polynomial optimization problems and their multilinear relaxations. Specifically, for the problems with Lp ball constraint, where P∈ [2 ,∞], by reducing them to that of determining the Lq-diameter of certain convex body, we show that they can be approximated to within a factor of [with formula] in deterministic polynomial time, where q = p=(p - 1) is the conjugate of p, n is the number of variables, and d is the degree of the polynomial. We further show that with the help of randomization, the approximation guarantee can be improved to [with formula], which is independent of p and is currently the best for the aforementioned problems. Moreover, we extend the argument of deterministic algorithm mentioned above to solve the quadratically constrained polynomial optimization problems. In particular, for any intersection of ellipsoids K, we can, in polynomial time, construct a random polytope P, which satisfies [with formula]. Then, by reducing the problem to that of evaluating the maximum polytopal norm [with formula] induced by P, over certain convex body, we can approximate the quadratically constrained problem within a factor of [with formula] in polynomial time. Our results unify and generalize those in the literature, which focus either on the quadratic case or the case where [with formula]. We believe that the wide array of tools used in this thesis will have further applications in the study of polynomial optimization problems.
Detailed summary in vernacular field only.
Hou, Ke.
On title page "p" is subscript.
Thesis (Ph.D.) Chinese University of Hong Kong, 2013.
Includes bibliographical references (leaves 106-111).
Abstracts also in Chinese.
"Cardinality constrained discrete-time linear-quadratic control." 2005. http://library.cuhk.edu.hk/record=b5892706.
Повний текст джерелаThesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 75-76).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Solution Framework Using Dynamic Programming --- p.7
Chapter 2.1 --- Difficulty of using dynamic programming --- p.8
Chapter 2.2 --- Scalar-state problems --- p.12
Chapter 2.3 --- Time-invariant system --- p.17
Chapter 2.4 --- Illustrative example of a scalar-state problem --- p.21
Chapter 3 --- Cardinality Constrained Quadratic Optimization --- p.26
Chapter 3.1 --- Reformulation --- p.27
Chapter 3.2 --- NP hardness --- p.31
Chapter 3.3 --- Solving CCQP with an efficient branch and bound method --- p.34
Chapter 3.3.1 --- Efficient branch and bound algorithm --- p.34
Chapter 3.3.2 --- Geometrical interpretation of the proposed ranking order --- p.48
Chapter 3.3.3 --- Additional algorithmic ideas for enhancing computational efficiency --- p.56
Chapter 3.4 --- Numerical example and computational results --- p.60
Chapter 4 --- Summary and Future Work --- p.73
"Distribution-free, uniformly-tighter linear approximations for chance-constrained programming." Sloan School of Management, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/2290.
Повний текст джерела"On cardinality constrained optimization." Thesis, 2009. http://library.cuhk.edu.hk/record=b6074943.
Повний текст джерелаGao, Jianjun.
Adviser: Duan Li.
Source: Dissertation Abstracts International, Volume: 72-11, Section: B, page: .
Thesis (Ph.D.)--Chinese University of Hong Kong, 2009.
Includes bibliographical references (leaves 134-142).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstract also in Chinese.
Yu-ChangTai and 戴毓璋. "Using Linear Programming to Solve Reliability-Constrained Task Scheduling in Computer Clusters." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/84933250090521038189.
Повний текст джерела國立成功大學
資訊工程學系
102
In parallel computing environment, the reliability is an important issue in the scheduling problem. Optimizing both finish time and reliability in task scheduling problem is a NP-complete problem. In order to increase the reliability of task scheduling, duplicating task is a very common technique. In this thesis, we propose a method of linear programming to find the most suitable duplication number of each task as possible, such that there is fastest finish time in the scheduling. Otherwise, the reliability must meet the requirement specified by users or systems. In this study, the reliability evaluation considers both processor and communication link. The reliability is a probability representing successful implementation of an application in computer clusters. Finally, the experimental results show that the presented algorithm outperforms other ones proposed.
"On safe tractable approximations of chance-constrained linear matrix inequalities with partly dependent perturbations." 2011. http://library.cuhk.edu.hk/record=b5894803.
Повний текст джерелаThesis (M.Phil.)--Chinese University of Hong Kong, 2011.
Includes bibliographical references (leaves 55-59).
Abstracts in English and Chinese.
Abstract --- p.i
Acknowledgement --- p.iii
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Preliminaries --- p.5
Chapter 2.1 --- Heuristics by Hoeffding and Janson --- p.5
Chapter 2.2 --- Facts in Matrix Theory --- p.10
Chapter 2.3 --- Facts in Probability --- p.11
Chapter 3 --- General Chance-Constrained LMIs --- p.18
Chapter 3.1 --- Probability Inequalities --- p.18
Chapter 3.2 --- Safe Tractable Approximations --- p.22
Chapter 4 --- Chance-Constrained Quadratically Perturbed LMIs --- p.27
Chapter 4.1 --- Exact Proper Fractional Covers --- p.27
Chapter 4.2 --- Bounding the Matrix Moment Generating Functions --- p.32
Chapter 5 --- Computational Study --- p.39
Chapter 5.1 --- Update Procedures for Safe Tractable Approximations --- p.39
Chapter 5.2 --- A Numerical Example and Comparisons --- p.44
Chapter 6 --- Conclusion --- p.54
Bibliography --- p.55
"Integration of constraint programming and linear programming techniques for constraint satisfaction problem and general constrained optimization problem." 2001. http://library.cuhk.edu.hk/record=b5890598.
Повний текст джерелаThesis (M.Phil.)--Chinese University of Hong Kong, 2001.
Includes bibliographical references (leaves 131-138).
Abstracts in English and Chinese.
Abstract --- p.ii
Acknowledgments --- p.vi
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Motivation for Integration --- p.2
Chapter 1.2 --- Thesis Overview --- p.4
Chapter 2 --- Preliminaries --- p.5
Chapter 2.1 --- Constraint Programming --- p.5
Chapter 2.1.1 --- Constraint Satisfaction Problems (CSP's) --- p.6
Chapter 2.1.2 --- Satisfiability (SAT) Problems --- p.10
Chapter 2.1.3 --- Systematic Search --- p.11
Chapter 2.1.4 --- Local Search --- p.13
Chapter 2.2 --- Linear Programming --- p.17
Chapter 2.2.1 --- Linear Programming Problems --- p.17
Chapter 2.2.2 --- Simplex Method --- p.19
Chapter 2.2.3 --- Mixed Integer Programming Problems --- p.27
Chapter 3 --- Integration of Constraint Programming and Linear Program- ming --- p.29
Chapter 3.1 --- Problem Definition --- p.29
Chapter 3.2 --- Related works --- p.30
Chapter 3.2.1 --- Illustrating the Performances --- p.30
Chapter 3.2.2 --- Improving the Searching --- p.33
Chapter 3.2.3 --- Improving the representation --- p.36
Chapter 4 --- A Scheme of Integration for Solving Constraint Satisfaction Prob- lem --- p.37
Chapter 4.1 --- Integrated Algorithm --- p.38
Chapter 4.1.1 --- Overview of the Integrated Solver --- p.38
Chapter 4.1.2 --- The LP Engine --- p.44
Chapter 4.1.3 --- The CP Solver --- p.45
Chapter 4.1.4 --- Proof of Soundness and Completeness --- p.46
Chapter 4.1.5 --- Compared with Previous Work --- p.46
Chapter 4.2 --- Benchmarking Results --- p.48
Chapter 4.2.1 --- Comparison with CLP solvers --- p.48
Chapter 4.2.2 --- Magic Squares --- p.51
Chapter 4.2.3 --- Random CSP's --- p.52
Chapter 5 --- A Scheme of Integration for Solving General Constrained Opti- mization Problem --- p.68
Chapter 5.1 --- Integrated Optimization Algorithm --- p.69
Chapter 5.1.1 --- Overview of the Integrated Optimizer --- p.69
Chapter 5.1.2 --- The CP Solver --- p.74
Chapter 5.1.3 --- The LP Engine --- p.75
Chapter 5.1.4 --- Proof of the Optimization --- p.77
Chapter 5.2 --- Benchmarking Results --- p.77
Chapter 5.2.1 --- Weighted Magic Square --- p.77
Chapter 5.2.2 --- Template design problem --- p.78
Chapter 5.2.3 --- Random GCOP's --- p.79
Chapter 6 --- Conclusions and Future Work --- p.97
Chapter 6.1 --- Conclusions --- p.97
Chapter 6.2 --- Future work --- p.98
Chapter 6.2.1 --- Detection of implicit equalities --- p.98
Chapter 6.2.2 --- Dynamical variable selection --- p.99
Chapter 6.2.3 --- Analysis on help of linear constraints --- p.99
Chapter 6.2.4 --- Local Search and Linear Programming --- p.99
Appendix --- p.101
Proof of Soundness and Completeness --- p.101
Proof of the optimization --- p.126
Bibliography --- p.130
Chen, Chan Hui, and 詹蕙珍. "The Resource-Constrained Multiple-Project Scheduling Problem with Multiple Fuzzy Objectives Non-linear Programming." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/09011704259285909618.
Повний текст джерела國立屏東科技大學
工業管理系
92
The purpose of this study is to develop a multiple fuzzy objective non-linear programming (MFONLP) model for solving the resource-constrained multi-project scheduling problem (RCMPSP). Two novel goals, maximization of total project net present value and the minimization of the total project duration, are involved in the RCMPSP model. Factors considered in the proposed model are the number of projects, the quantity of renewable-resources available, the quantity of capital available, multiple objective functions, the project delay penalty and the project early completion bonus. By using these factors as objective trade-off components with multiple fuzzy goals, the proposed model is practically developed to provide various scenarios on specific satisfactory levels. Two project-scheduling cases are implemented to test the proposed model. The implementation is designed as several scenarios to determine the objective variations of goal components. The implementation results demonstrate that the use of MFONLP models could provide project manager with further insight into the systematic analysis. Furthermore, an evaluation is conducted to compare the effectiveness between the proposed model with the goal programming model and Zimmermann model. The comparison results demonstrate that the MFONLP model yields a higher total project net present value and a lower total project duration than that the two existing models do. The proposed MFONLP model also demonstrates more flexibility for application to the RCMPSP-DCF, which is useful for project manager while making decisions.
Espinoza, Francisco. "A New Interpolation Approach for Linearly Constrained Convex Optimization." Thesis, 2012. http://hdl.handle.net/10754/244891.
Повний текст джерелаChen, Chien-Chu, and 陳建助. "Application of Fuzzy Multi-Objective Linear Programming on the Robust Resource-Constrained Multi-Project Scheduling Problems." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/76354092911141579847.
Повний текст джерела國立屏東科技大學
工業管理系所
97
The purpose of this study is to formulate a fuzzy multiobjective non-linear programming (FMONLP) model to solve the robust resource-constrained multi-project scheduling problems (RRCMPSP). Project slack time and maximization robustness are considered as factors in terms of project resources and capital limitation in the proposed model. An optimal satisfactory level is deployed to demonstrate the trade-offs among fuzzy multi-objectives for the use of project managers. The implementation is designed as several aspects to demonstrate the parameter variations of FMONLP and its superior to previous models. The implementation results also demonstrate that the use of FMONLP to solve RRCMPSP could help project managers explain to the theoretical rigor not found in simpler decision models for project management.
Guindon, David Leo. "Design of nearly linear-phase recursive digital filters by constrained optimization." Thesis, 2007. http://hdl.handle.net/1828/296.
Повний текст джерелаWang, Lin-In, and 王玲英. "An Application of Gray Linear Programming to Power Plant Expansion Strategies as Constrained by Ambient Air Quality." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/78691907252627844601.
Повний текст джерела逢甲大學
環境工程與科學所
91
The growing demand of electricity in recent years in Taiwan is a result of high-tech industry expansions and living standard enhancement. To meet increasing demand generating capacity (particularly coal-fired power plants) will have to increase. Expansions in power production will place additional burden on the environment in terms of air pollution. Therefore, it is imperative to expand generating capacity while maintaining environmental quality. The objective of this research is to identify the best expansion strategies of coal-fired power plants as constrained by the ambient air quality. Major substances of the research are Apply an air quality model to calculate the ambient air quality effects resulting from an increase of one unit of generator at a power plant (call these effects as transfer coefficients) Adopt the gray linear programming technique to identify the number of generating units (integers) allowable at each power plant under the constraint of air quality standard Include the concept of prevention of significant deterioration of ambient air quality in expansion strategies Perform the sensitivity analysis─the increase of extra generating capacity when the emissions from power plant stacks are reduced The research selected the central region of Taiwan as a case study. Results of the study ascertain the feasibility and validity of the research concept.
Adeyefa, Segun Adeyemi. "Satisticing solutions for multiobjective stochastic linear programming problems." Thesis, 2011. http://hdl.handle.net/10500/5703.
Повний текст джерелаDecision Sciences
Adeyefa, Segun Adeyemi. "Satisficing solutions for multiobjective stochastic linear programming problems." Thesis, 2011. http://hdl.handle.net/10500/5703.
Повний текст джерелаDecision Sciences