1,627 research outputs found

    The double traveling salesman problem with partial last-in-first-out loading constraints

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    In this paper, we introduce the double traveling salesman problem with partial last-in-first-out loading constraints (DTSPPL). It is a pickup-and-delivery single-vehicle routing problem, where all pickup operations must be performed before any delivery operation because the pickup-and-delivery areas are geographically separated. The vehicle collects items in the pickup area and loads them into its container, a horizontal stack. After performing all pickup operations, the vehicle begins delivering the items in the delivery area. Loading and unloading operations must obey a partial last-in-first-out (LIFO) policy, that is, a version of the LIFO policy that may be violated within a given reloading depth. The objective of the DTSPPL is to minimize the total cost, which involves the total distance traveled by the vehicle and the number of items that are unloaded and then reloaded due to violations of the standard LIFO policy. We formally describe the DTSPPL through two integer linear programming (ILP) formulations and propose a heuristic algorithm based on the biased random-key genetic algorithm (BRKGA) to find high-quality solutions. The performance of the proposed solution approaches is assessed over a broad set of instances. Computational results have shown that both ILP formulations have been able to solve only the smaller instances, whereas the BRKGA obtained good-quality solutions for almost all instances, requiring short computational times

    Mathematical models and heuristic algorithms for routing problems with multiple interacting components.

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    Programa de P?s-Gradua??o em Ci?ncia da Computa??o. Departamento de Ci?ncia da Computa??o, Instituto de Ci?ncias Exatas e Biol?gicas, Universidade Federal de Ouro Preto.Muitos problemas de otimiza??o com aplica??es reais t?m v?rios componentes de intera??o. Cada um deles pode ser um problema pertencente ? classe N P-dif?cil, e eles podem estar em conflito um com o outro, ou seja, a solu??o ?tima para um componente n?o representa necessariamente uma solu??o ?tima para os outros componentes. Isso pode ser um desafio devido ? influ?ncia que cada componente tem na qualidade geral da solu??o. Neste trabalho, foram abordados quatro problemas de roteamento complexos com v?rios componentes de intera??o: o Double Vehicle Routing Problem with Multiple Stacks (DVRPMS), o Double Traveling Salesman Problem with Partial Last-InFirst-Out Loading Constraints (DTSPPL), o Traveling Thief Problem (TTP) e Thief Orienteering Problem (ThOP). Enquanto os DVRPMS e TTP j? s?o bem conhecidos na literatura, os DTSPPL e ThOP foram recentemente propostos a fim de introduzir e estudar variantes mais realistas dos DVRPMS e TTP, respectivamente. O DTSPPL foi proposto a partir deste trabalho, enquanto o ThOP foi proposto de forma independente. Neste trabalho s?o propostos modelos matem?ticos e/ou algoritmos heur?sticos para a solu??o desses problemas. Dentre os resultados alcan?ados, ? poss?vel destacar que o modelo matem?tico proposto para o DVRPMS foi capaz de encontrar inconsist?ncias nos resultados dos algoritmos exatos previamente propostos na literatura. Al?m disso, conquistamos o primeiro e o segundo lugares em duas recentes competi??es de otimiza??o combinat?ria que tinha como objetivo a solu??o de uma vers?o bi-objetiva do TTP. Em geral, os resultados alcan?ados por nossos m?todos de solu??es mostraram-se melhores do que os apresentados anteriormente na literatura considerando cada problema investigado neste trabalho.I would like to express my greatest thanks to my parents, Jo?o Batista and Adelma, and my sister, Jaqueline, for their wise counsel. They have always supported me and given me the strength to continue towards my goals. To Bruna Vilela, I am grateful for her fondness, for always listening to my complaints, and for celebrating with me my personal and academic achievements. I love you all demais da conta1 ! Throughout the writing of this thesis, I have received great assistance. I would like to acknowledge my advisors, Prof. Ph.D. Marcone J. F. Souza, and Prof. Ph.D. Andr? G. Santos, for their support and guidance over these years. I would also like to thank all the authors who have contributed to the research papers produced from this work, in particular, to Prof. Ph.D. Markus Wagner for his great collaboration in some of my projects. I would like to thank Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES), and Universidade Federal de Ouro Preto (UFOP) for funding this project. I thank the Universidade Federal de Vi?osa (UFV) for receiving me as a collaborating researcher over these last two years. I could not but offer up my thanks to the HassoPlattner-Institut (HPI) Future SOC Lab, the Divis?o de Suporte ao Desenvolvimento Cient?fico e Tecnol?gico (DCT/UFV), and the Programa de P?s-gradua??o em Ci?ncia da Computa??o (PPGCC/UFOP) for enabling this research by providing access to their computing infrastructure

    Container Hinterland Drayage - On the Simultaneous Transportation of Containers Having Different Sizes

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    In an intermodal transportation chain drayage is the term used for the movement by truck of cargo that is filled in a loading unit. The most important intermodal transportation chain is the intermodal container transportation, in which containers represent the loading unit for cargo. Cost effectiveness constitutes a general problem of drayage operations. A major cost driver within container transportation chains is the movement and repositioning of empty containers. The present thesis investigates the potential to reduce drayage costs. Two solution methodologies are developed for operating a fleet of trucks that transports containers of different sizes, which addresses a recent gap in research in seaport hinterland regions

    Algorithmic Solutions for Combinatorial Problems in Resource Management of Manufacturing Environments

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    This thesis studies the use of heuristic algorithms in a number of combinatorial problems that occur in various resource constrained environments. Such problems occur, for example, in manufacturing, where a restricted number of resources (tools, machines, feeder slots) are needed to perform some operations. Many of these problems turn out to be computationally intractable, and heuristic algorithms are used to provide efficient, yet sub-optimal solutions. The main goal of the present study is to build upon existing methods to create new heuristics that provide improved solutions for some of these problems. All of these problems occur in practice, and one of the motivations of our study was the request for improvements from industrial sources. We approach three different resource constrained problems. The first is the tool switching and loading problem, and occurs especially in the assembly of printed circuit boards. This problem has to be solved when an efficient, yet small primary storage is used to access resources (tools) from a less efficient (but unlimited) secondary storage area. We study various forms of the problem and provide improved heuristics for its solution. Second, the nozzle assignment problem is concerned with selecting a suitable set of vacuum nozzles for the arms of a robotic assembly machine. It turns out that this is a specialized formulation of the MINMAX resource allocation formulation of the apportionment problem and it can be solved efficiently and optimally. We construct an exact algorithm specialized for the nozzle selection and provide a proof of its optimality. Third, the problem of feeder assignment and component tape construction occurs when electronic components are inserted and certain component types cause tape movement delays that can significantly impact the efficiency of printed circuit board assembly. Here, careful selection of component slots in the feeder improves the tape movement speed. We provide a formal proof that this problem is of the same complexity as the turnpike problem (a well studied geometric optimization problem), and provide a heuristic algorithm for this problem.Siirretty Doriast

    Optimization for Decision Making II

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    In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner
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