Domination and Decomposition in Multiobjective Programming

During the last few decades, multiobjective programming has received much attention for both its numerous theoretical advances as well as its continued success in modeling and solving real-life decision problems in business and engineering. In extension of the traditionally adopted concept of Pareto optimality, this research investigates the more general notion of domination and establishes various theoretical results that lead to new optimization methods and support decision making. After a preparatory discussion of some preliminaries and a review of the relevant literature, several new findings are presented that characterize the nondominated set of a general vector optimization problem for which the underlying domination structure is defined in terms of different cones. Using concepts from linear algebra and convex analysis, a well known result relating nondominated points for polyhedral cones with Pareto solutions is generalized to nonpolyhedral cones that are induced by positively homogeneous functions, and to translated polyhedral cones that are used to describe a notion of approximate nondominance. Pareto-oriented scalarization methods are modified and several new solution approaches are proposed for these two classes of cones. In addition, necessary and sufficient conditions for nondominance with respect to a variable domination cone are developed, and some more specific results for the case of Bishop-Phelps cones are derived. Based on the above findings, a decomposition framework is proposed for the solution of multi-scenario and large-scale multiobjective programs and analyzed in terms of the efficiency relationships between the original and the decomposed subproblems. Using the concept of approximate nondominance, an interactive decision making procedure is formulated to coordinate tradeoffs between these subproblems and applied to selected problems from portfolio optimization and engineering design. Some introductory remarks and concluding comments together with ideas and research directions for possible future work complete this dissertation

Eco-efficient Supply Chains for Electrical and Electronic Products

Hundreds of millions of electrical and electronic appliances are manufactured every year. Furthermore, it is expected that this number will not substantially decrease in the near future. These equipments have a significant impact on the environment, and ceteris paribus, such environmental impact increases with the number of appliances manufactured. Consumers, NGOs and Governments have acknowledged the potential threat posed by these electrical and electronic products. They have systematically demanded companies to reduce the environmental impact caused be their products and services. Companies have responded to these pressures and have engaged in a number of environmentally friendly initiatives. This thesis is motivated by the task of reducing the environmental impact caused by the myriad of electrical and electronic products that make our lives more conformable and enjoyable. More specifically, it addresses the challenge of efficiently and effectively mitigating such impacts. We show that companies will need a mixture of strategies to respond to this challenge. Furthermore, we show that these strategies must consider environmental, technical and marketing aspects of the business of electrical and electronic products. These three aspects need to be considered systemically, and the solutions will vary greatly according to the companies, the products they manufacture, and the ways in which their supply chains are organized

New extesions of the scalarizations techiques in the multiobjective one-dimensional cutting stock problem

Orientador: Antonio Carlos MorettiTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação CientíficaResumo: O presente trabalho trata do Problema de Corte Unidimensional Inteiro Multiobjetivo (PCUIM). Este problema possui uma importância prática enorme e a sua abordagem multiobjetiva foi pouco reportada na literatura. O modelo biobjetivo considerado visa minimizar a soma das frequências dos padrões de corte para atender à mínima demanda e ao número de diferentes padrões a serem usados (\textit{setup}), sendo estas metas conflitantes entre si. Neste caso, o PCUIM possui um conjunto não unitário de soluções, ditas de \textit{soluções eficientes}, todas igualmente importantes para o problema. A geração de cada solução eficiente necessita a otimização de um Problema de Programação Linear Inteiro e a obtenção de todas estas soluções pode ser uma tarefa relativamente cara, principalmente quando os padrões de corte não são fornecidos pelo usuário a priori. Nesta tese, foram utilizados sete métodos distintos que transformam o PCUIM em problemas de otimização escalares, que por sua vez, geram as soluções eficientes. Seis métodos foram adaptados da literatura e um foi originalmente desenvolvido. A fim de acelerar a obtenção do conjunto de soluções eficientes, no caso com os padrões fornecidos pelo usuário, foi adotada uma estratégia que relaxa as condições de integralidade das variáveis do problema e, posteriormente, cada solução eficiente produzida é integralizada por meio de uma heurística ineditamente desenvolvida. Os extensos testes computacionais presentes no Capítulo 8, comprovaram que esta ideia foi adequada e eficaz. Além disso, a nova técnica de escalarização se mostrou muito competitiva com as demais consagradas na literatura, possibilitando um crescimento e um avanço na área de Problemas de Corte bem como na Otimização Combinatória MultiobjetivoAbstract: The present work deals with the Multiobjective One-Dimensional Cutting Stock Problem (MODCSP). This problem has an enormous practical importance, and the multiobjective approach has been little reported in the literature. The bi-objective model considered aims to minimize the sum of the frequency of cutting patterns to meet minimal demand and the number of different cutting patterns to be used (setup), being these objectives conflicting. In this case, the MODCSP has a non-unitary set of solutions, said \textit{efficient solutions}, equally important for the problem. The generation of each efficient solution requires the optimization of an Integer Linear Problem. So, the complete enumeration of these solutions can be an expensive task, especially when cutting patterns are not provided by the user. In this thesis, we applied seven different methods that transform the MODCSP on scalar optimization problems, where each problem provide an efficient solution. Six scalarization methods were adapted from literature and one was unprecedentedly developed. In the case of the cutting patterns be provided a priori, we used a relaxation strategy (heuristic) to accelerate obtaining of the set efficient solutions. In this approach, we relaxed the integrality condition of the variables and each efficient solution was rounded by a specially developed heuristic. The extensive results in Chapter 8 validated that this idea was adequate and effective. Furthermore, the new scalarization technique proved to be very competitive with other established in the literature, enabling growth and advancement in the area of the Cutting Problems and in Multiobjective Combinatorial OptimizationDoutoradoMatematica AplicadaDoutor em Matemática Aplicada2013/06035-0FAPESPCAPE