O sequenciamento e a programação da produção trazem grandes benefícios financeiros às empresas se realizados de forma adequada. Atualmente, soluções generalizadas apresentam resultados aceitáveis, porém têm como consequência benefícios inferiores quando comparados a estudos específicos. O ramo da otimização de resultados possui dois tipos de soluções: as exatas para problemas de menores dimensões e não exatas, ou heurísticas, para problemas de médias e grandes dimensões. Este trabalho apresenta algoritmos exatos do tipo Branch & Bound e Modelos de Programação Linear Inteira Mista para solucionar quatro variações de problemas de scheduling: Fm|block|∑Cjm, Fm|block|∑Tj, Fm|block, Sijk|∑Cjm e Fm|block, Sijk|∑Tj. As abordagens utilizadas são inéditas na literatura e apresentaram resultados animadores para a maioria dos cenários. O limitante para o tempo total de fluxo obteve resposta ótima em 100% dos casos para problemas de até 20 tarefas e 4 máquinas em menos de uma hora. Para o tempo total de atraso, o limitante se mostrou mais eficiente quando os valores das due dates apresentam alta taxa de dispersão. Para os casos com setup, foram elaboradas três variações de limitantes para cada problema. O limitante com setup que apresentou o melhor desempenho foi o que obteve a melhor relação entre o seu valor numérico e seu custo computacional. Os modelos MILP solucionaram 100% dos problemas sem setup para até 20 tarefas e 4 máquinas e para os casos com setup, foram solucionados problemas de até 14 tarefas e 4 máquinas no tempo limite de uma hora. Os testes computacionais mostram a eficiência na redução do número de nós e, consequentemente, no tempo de execução. Portanto, o estudo realizado indica que, para problemas de pequeno porte e médio, os métodos em questão possuem grande potencial para aplicações práticas. / Job Sequence and Programming give benefits both financial and organizational to any company when performed properly. Nowadays, there is still a gap between theory and practice due to solutions that are short in specification. The analyzed problems differ in type and dimension thus modifying its complexity. The results optimization field is divided into two types of solution: the exact solution for minor problems and the non-exact solution for greater dimension problems. The present paper presents exact algorithms to solve the problems Fm|block|∑Cjm, Fm|block|∑Tj, Fm|block, Sijk|∑Cjm by the Branch & Bounds and Mixed Integer Linear Program models. The approaches are new and presented good results for most cases. Bounds for the no-setup total flow time scenario solved 100% of the 20 jobs and 4 machines cases. High dispersion range due dates contributed for the effectiveness of the no-setup total tardiness bound\'s effectiveness. Three different approaches were developed for the setup cases. The best approach aimed to optimize the value/effort factor for the B&B. The Mixed Integer Linear Program models solved 100% of the no-setup cases for 20 jobs and 4 machines. The MILPs setup cases solved optimally 14 jobs and 4 machines cases. Computational tests were executed and analyzed and they highlighted the node count reduction and, consequently, the execution time. The present study points out that the exact methods can be applied to small and medium scheduling problems in practice.

Orientador: Francisco de Assis Magalhães Gomes Neto / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica / Made available in DSpace on 2018-08-25T19:03:25Z (GMT). No. of bitstreams: 1 Villela_PedroFerraz_D.pdf: 10794575 bytes, checksum: 746b8aebf0db423d557d9c5fe1446592 (MD5) Previous issue date: 2014 / Resumo: Neste trabalho, propomos um método exato para obter o conjunto solução de um problema biobjetivo quadrático de otimização de carteiras de investimento, que envolve variáveis binárias. Nosso algoritmo é baseado na junção de três algoritmos específicos. O primeiro encontra uma curva associada ao conjunto solução de problemas biobjetivo contínuos por meio de um método de restrições ativas, o segundo encontra o ótimo de um problema de programação quadrática inteira mista pelo método Branch-and-Bound, e o terceiro encontra a interseção de duas curvas associadas a problemas biobjetivo distintos. Ao longo do texto, algumas heurísticas e métodos adicionais também são introduzidos, com o propósito de acelerar a convergência do algoritmo proposto. Além disso, o nosso método pode ser visto como uma nova contribuição na área, pois ele determina, de forma exata, a curva associada ao conjunto solução do problemas biobjetivo inteiro misto, algo que é incomum na literatura, pois o problema alvo geralmente é abordado via métodos meta-heurísticos. Ademais, ele mostrou ser eficiente do ponto de vista do tempo computacional, pois encontra o conjunto solução do problema em poucos segundos / Abstract: In this work, we propose an exact method to find the solution set of a mixed quadratic bi-objective portfolio optimization problem. Our method is based on the combination of three specific algorithms. The first one obtains a curve associated with the solution set of a continuous bi-objective problem through an active set algorithm, the second one solves a mixed quadratic optimization problem through the Branch-and-Bound method, and the third one searches the intersection of two curves associated with distinct bi-objective problems. Throughout the text, some heuristics are also introduced in order to accelerate the performance of the method. Moreover, our method can be seen as a new contribution to the field, since it finds, in an exact way, the curve related to the solution set of the mixed integer bi-objective problem, something uncommon in the corresponding literature, where the target problem is usually approached by metaheuristic methods. Additionally, it has also shown to be efficient in terms of running time, being capable of finding the problem's solution set within a much faster time frame / Doutorado / Matematica Aplicada / Doutor em Matemática Aplicada

Notre objectif dans cette thèse est de proposer des algorithmes efficaces pour résoudre des problèmes d’optimisation combinatoire difficiles. Dans un premier temps, nous établissons le principe de l’énumération ordonnée qui consiste à générer dans un ordre adéquat les solutions d’un problème relâché associé au problème principal jusqu’à l’obtention de la preuve d’optimalité d’une solution. Nous construisons une procédure générique dans le cadre général des problème d’optimisation combinatoire. Dans un second temps nous abordons les applications de notre algorithme sur des problèmes qui admettent le problème d’affectation comme relaxation. Le premier cas particulier que nous étudions est la recherche d’une solution de bon compromis pour le problème d’affectation multiobjectif. La seconde application se rapporte au problème du voyageur de commerce asymétrique qui présente la difficulté de comporter des contraintes qui interdisent les sous-tournées, en plus des contraintes du problème d’affectation. / Our aim in this thesis is to propose efficient algorithms for solving difficult combinatorial optimization problems. Our algorithms are based on a generic method of ordered enumeration. Initially, we describe the principle of ordered enumeration which consists in generating in a specific order solutions of a relaxed problem associated to the difficult main problem, until meeting a proof of the optimality of a feasible solution. We construct a generic procedure in the general context of combinatorial optimization problems. In a second step we discuss applications of our algorithm on some difficult problems which admit the assignment problem as relaxation. The first special case we study is the search for a compromise solution to the multiobjective assignment problem. The second application is the asymmetric travelling salesman problem, which contains sub-tour constraints in addition to the constraints of the assignment problem.

L’industrie forestière est un secteur qui, même s’il est en déclin, se trouve au cœur du débat sur la mondialisation et le développement durable. Pour de nombreux pays tels que le Canada, la Suède et le Chili, les objectifs sont de maintenir un secteur florissant sans nuire à l’environnement et en réalisant le caractère fini des ressources. Il devient important d’être compétitif et d’exploiter de manière efficace les territoires forestiers, de la récolte jusqu’à la fabrication des produits aux usines, en passant par le transport, dont les coûts augmentent rapidement. L’objectif de ce mémoire est de développer un modèle de planification tactique/opérationnelle qui permet d’ordonnancer les activités pour une année de récolte de façon à satisfaire les demandes des usines, sans perdre de vue le transport des quantités récoltées et la gestion des inventaires en usine. L’année se divise en 26 périodes de deux semaines. Nous cherchons à obtenir les horaires et l’affectation des équipes de récolte aux blocs de coupe pour une année. Le modèle mathématique développé est un problème linéaire mixte en nombres entiers dont la structure est basée sur chaque étape de la chaine d’approvisionnement forestière. Nous choisissons de le résoudre par une méthode exacte, le branch-and-bound. Nous avons pu évaluer combien la résolution directe de notre problème de planification était difficile pour les instances avec un grand nombre de périodes. Cependant l’approche des horizons roulants s’est avérée fructueuse. Grâce à elle en une journée, il est possible de planifier les activités de récolte des blocs pour l’année entière (26 périodes). / Forest industry is a sector located at the heart of the debate on globalisation and sustainable development, even if it is in decline. For many countries like Canada, Sweden and Chile, the objectives are to maintain a flourishing sector without damaging the environment and to realize the finite nature of resources. It is important to be competitive and to operate effectively on forest territories, from harvesting to manufacturing products, through transport, in a context where costs increase rapidly. This master’s thesis is developing a tactical operational planning model to organize activities for a year to meet requests for factories, without losing sight of the transport of harvested quantities and inventory management factory. The year is divided into 26 periods of two weeks. We seek harvest teams schedules and assignment to harvest areas (units) for a year. The problem is formulated as a mixed integer programming model, whose structure is based on each stage of the forest supply chain. We choose to solve it by an exact method, branch-and-bound. We were able to assess how the direct resolution of our planning problem was difficult for instances with a large number of periods. However the rolling horizon approach has proved successful. In a day, we obtained the harvest activities planning for 26 periods.

Darbe apžvelgiama trimačio pakavimo problemos tipologija. Nagrinėjama trimečio konteinerių pakavimo problema ir jos sprendimo būdai. Pateikiama šakos ir ribos, bei tabu paieškos algoritmų formulavimas ir jų rezultatų analizė. / The paper gives an overview of three-dimensional packing problem typology. There are investigating issue of container packing problem and its solutions. Branch and bound, TSpack algorithms formulation and analysis of their results.

Made available in DSpace on 2015-03-04T18:50:48Z (GMT). No. of bitstreams: 1 THESIS.pdf: 364289 bytes, checksum: f8df107da6c5e647683554fbbc63f7a5 (MD5) Previous issue date: 2007-03-01 / Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / The use of quantum systems as part of the communication systems has been source of interesting problems many without solution. In the present work, we show the basic concepts of information theory and quantum mechanics necessary to understand the accessible information problem, whose solution maximizes the Shannon mutual information for a channel defined by an ensemble of quantum states given a priori. In order to estimate more precise bounds for accessible information, we propose the use of Branch and Bound method with interval arithmetic. Numerical experiments and related results are exhibited. / O uso de sistemas quâticos como parte de sistemas de comunicação tem sido fonte de interessantes problemas muitos ainda sem solução. No presente trabalho, apresentamos os conceitos básicos em teoria da informação e mecânica quântica necessários ao entendimento do problema do cálculo da informação acessível, cuja solução maximiza a informação mútua de Shannon para um canal definido por um ensemble de estados quâticos dados a priori. Propomos o uso do método de otimização global Branch and Bound aliado à aritmética intervalar para a estimação de limites mais precisos que os teóricos disponíveis para a informação acessível. Experimentos numéricos e resultados relacionados são apresentados.

A diferença entre estações de trabalho é considerada desprezível em linhas de montagem tradicionais. Por outro lado, linhas de montagem heterogêneas consideram o problema de indústrias nas quais os tempos das tarefas variam de acordo com alguma característica a ser selecionada para a tarefa. No Problema de Balanceamento e Atribuição de Trabalhadores em Linhas de Montagem (do inglês Assembly Line Worker Assignment and Balancing Problem, ALWABP), os trabalhadores são responsáveis por estações de trabalho e de acordo com as suas habilidades, eles executam as tarefas em diferentes quantidades de tempo. Em alguns casos, os trabalhadores podem até ser incapazes de executar algumas tarefas. No Problema de Balanceamento de Linhas de Montagem Robóticas (do inglês Robotic Assembly Line Balancing Problem, RALBP), há diferentes tipos de robôs e o conjunto de tarefas de cada estação deve ser executada por um robô. Robôs do mesmo tipo podem ser usados múltiplas vezes. Nós propomos métodos exatos e heurísticos para a minimização do tempo de ciclo destes dois problemas, para um número fixo de estações. Os problemas têm características similares que são exploradas para produzir limitantes inferiores, métodos inferiores, models de programação inteira mista, e regras de redução e dominância. Para a estratégia de ramificação do método de branch-and-bound, entretanto, as diferenças entre os problemas forçam o uso de dois algoritmos diferentes. Uma estratégia orientada a tarefas tem os melhores resultados para o ALWABP-2, enquanto uma estratégia orientada a estações tem os melhores resultados para o RALBP-2. Nós mostramos que os limitantes inferiores, heurísticas, modelos de programação inteira mista e algoritmos de branch-and-bound para estes dois problemas são competitivos com os métodos do estado da arte da literatura. / The difference among workstations is assumed to be negligible in traditional assembly lines. Heterogeneous assembly lines consider the problem of industries in which the task times vary according to some property to be selected for the task. In the Assembly Line Worker Assignment and Balancing Problem (ALWABP), workers are assigned to workstations and according to their abilities, they execute tasks in different amounts of time. In some cases they can even be incapable of executing some tasks. In the Robotic Assembly Line Balancing Problem (RALBP) there are different types of robots and each station must be executed by a robot. Multiple robots of the same type may be used. We propose exact and heuristic methods for minimizing the cycle time of these two problems, for a fixed number of stations. The problems have similar characteristics that are explored to produce lower bounds, heuristic methods, mixed-integer programming models, and reduction and dominance rules. For the branching strategy of the branch-and-bound method, however, the differences among the problem force the use of two different algorithms. A task-oriented strategy has the best results for the ALWABP-2 while a station-oriented strategy has the best results for the RALBP-2. The lower bounds, heuristics, MIP models and branch-and-bound algorithms for these two problems are shown to be competitive with the state-of-the-art methods in the literature.

In this paper, we minimize the holding cost of the safety stock in the supply chain subject to linear constraints on the service times between the nodes of the network. In the problem, the objective function is concave as we assume the demand to be bounded by a concave function. The optimal solutions of the problem belong to the set of extreme points of the polyhedron, specified by the constraints of the problem. We first characterize the extreme points for the two-layer networks and then provide bounds to use in a branch and bound algorithm. / Singapore-MIT Alliance (SMA)

The purpose of this research is to develop a model and solution methodology for selecting and scheduling timely and cost-effective maintenance, rehabilitation, and reconstruction activities (M & R) for each pavement section in a highway network and allocating the funding levels through a finite multi-period horizon within the constraints imposed by budget availability in each period, frequency availability of activities, and specified minimum pavement quality requirements. M & R is defined as a chronological sequence of reconstruction, rehabilitation, and major/minor maintenance, including a "do nothing" activity. A procedure is developed for selecting an M & R activity for each pavement section in each period of a specified extended planning horizon. Each activity in the sequence consumes a known amount of capital and generates a known amount of effectiveness measured in pavement quality. The effectiveness of an activity is the expected value of the overall gains in pavement quality rating due to the activity performed on a highway network over an analysis period. It is assumed that the unused portion of the budget for one period can be carried over to subsequent periods. Dynamic Programming (DP) and Branch-and-Bound (B-and-B) approaches are combined to produce a hybrid algorithm for solving the problem under consideratioin. The algorithm is essentially a DP approach in the sense that the problem is divided into smaller subproblems corresponding to each single period problem. However, the idea of fathoming partial solutions that could not lead to an optimal solution is incorporated within the algorithm to reduce storage and computational requirements in the DP frame using the B-and-B approach. The imbedded-state approach is used to reduce a multi-dimensional DP to a one-dimensional DP. For bounding at each stage, the problem is relaxed in a Lagrangean fashion so that it separates into longest-path network model subproblems. The values of the Lagrangean multipliers are found by a subgradient optimization method, while the Ford-Bellman network algorithm is employed at each iteration of the subgradient optimization procedure to solve the longest-path network problem as well as to obtain an improved lower and upper bound. If the gap between lower and upper bound is sufficiently small, then we may choose to accept the best known solutions as being sufficiently close to optimal and terminate the algorithm rather than continue to the final stage.

Majority of the studies in the scheduling literature is devoted to time based performance measures. In this thesis, we develop a model that considers monetary issues in single machine scheduling environments. We assume all the jobs should be completed by a common due date. An early revenue is earned if the completion time is before or on the due date, and a tardy revenue is gained if the job is completed after the due date. We consider restricted and unrestricted due date versions of the problem. Our objective is the maximization of the net present value of all revenues. We first investigate some special cases of the problem, and present polynomial time algorithms to solve them. Then, we develop branch and bound algorithms with lower and upper bounding mechanisms. Computational experiments have shown that the branch and bound algorithms can solve large-sized problems in reasonable times.