Desenvolvimento de um método metaheurístico híbrido algoritmo genético- busca tabu para o problema de programação de operações flow-shop permutacional

• Ano de defesa: 2000
• Autor(a) principal: Souza, Angela Betania Dias de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: flow shop sequencing; hybrid metaheuristics; production scheduling
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/18/18140/tde-28052024-092402/

This work deals with the permutation flow shop scheduling problem. This problem is considered NP-hard, that is, of dificult solution, this is why several heuristic methods are seen in the literature for the solution o f such a problem. The advantage o f using heuristics methods is that they provide a good solution and some times optimal, with a computational time relatively small. The Genetic Algorithm (GA) and the Tabu Search (TS) techniques are heuristics methods that improve the inicial solutions of the problem beginning with the procedure of search in the space of solutions. A promissing idea that shows up in the literature, refers to the development of hybrid heuristic methods, for example, the metaheuristics AG and BT. The objective of combining metaheuristic techniques is to obtain a hybrid methodwhich is more effective than the ones used individually. In this work we present a hybrid heuristic method Genetic Algorithm-Tabu Search,jor short HBGATS, for the minimal makespan jlow shop sequencing problem. To evaluate the performance of the hybridsation, we compare the performance ofthe hybrid methodwith those ofthe pure AG and BTwich were used in the hybridsation. The results obtained in the computational experimentation are checked, and a conclusion got about the performance of the hybrid HBGATS method in relation to the pures.