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

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

Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm

In any metaheuristic, the parameter values strongly affect the efficiency of an algorithm’s search. This research aims to find the optimal parameter values for the Pareto Ant Colony System (PACS) algorithm, which is used to obtain solutions for the generator maintenance scheduling problem. For optimal maintenance scheduling with low cost, high reliability, and low violation, the parameter values of the PACS algorithm were tuned using the Taguchi and Gray Relational Analysis (Taguchi-GRA) method through search-based approach. The new parameter values were tested on two systems. i.e., 26- and 36-unit systems for window with operational hours [3000-5000]. The gray relational grade (GRG) performance metric and the Friedman test were used to evaluate the algorithm’s performance. The Taguchi-GRA method that produced the new values for the algorithm’s parameters was shown to be able to provide a better multi-objective generator maintenance scheduling (GMS) solution. These values can be benchmarked in solving multi-objective GMS problems using the multi-objective PACS algorithm and its variants

Ants can orienteer a thief in their robbery

The Thief Orienteering Problem (ThOP) is a multi-component problem that combines features of two classic combinatorial optimization problems: Orienteering Problem and Knapsack Problem. The ThOP is challenging due to the given time constraint and the interaction between its components. We propose an Ant Colony Optimization algorithm together with a new packing heuristic to deal individually and interactively with problem components. Our approach outperforms existing work on more than 90% of the benchmarking instances, with an average improvement of over 300%.Jonatas B.C. Chagas, Markus Wagne