Uma estrutura de vizinhança baseada em árvore de cobertura aplicada em uma colaboração de algoritmo genético e VNS para a minimização de makespan em problemas de programação reativa da produção

• Ano de defesa: 2015
• Autor(a) principal: Tuma, Carlos Cesar Mansur
• Orientador(a): Morandin Júnior, Orides
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação - PPGCC
• Palavras-chave em Português: Árvore de cobertura; Estrutura de vizinhança; Programação reativa da produção; Colaboração global-local
• Palavras-chave em Inglês: Makespan; Neighborhood structure; Reactive scheduling; Spanning tree; Global-local collaboration
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/7522

The generation of Reactive Production Scheduling (PRP) in order to minimize the makespan is an important activity in the manufacturing industry, in view of the numerous articles reflecting this search today. Among these studies highlight the global search use in hybridization or collaboration with local search, especially of Genetic Algorithm (GA) with Variable Neighborhood Search (VNS). But see that the neighborhood structures used are not related to the goal of makespan minimization or when they are, are difficult to obtain. In order to cover this topic, this thesis proposes the hypothesis that a strongly correlated neighborhood structure with objective of makespan minimization in PRP problems, based on spanning tree, and applied on a collaboration among a genetic algorithm with VNS, perform better or equal to those obtained by other studies using other neighborhood structures or without the use of local search. The purpose was to construct a collaboration of GA and VNS using a neighborhood structure based on the mapping of the solution in the spanning tree associated with the problem, in the local search time, and operating with the insert, swap and 2-opt operators. The planning of experiments for validation contemplated since the implementation and comparison of four variants of reactive production scheduling in three job shop scenarios of different sizes. Each pair of comparisons had its calculated sample size and has been tested with the appropriate hypothesis test. The four variants were compared: Genetic Algorithm only and three collaborations of GA with VNS using the neighborhood structure proposal and two other neighborhood structures (Critical Path and Natural Representation) found in the literature review. The scenarios came from Taillard base. The tests corroborate the hypothesis, with 95% confidence, compared to other works and the main contribution of this thesis is to create an efficient method for minimizing makespan in PRP.