Aplicação de algoritmos genéticos para minimização do número de objetos processados e o setup num problema de corte unidimensional

• Autor(a) principal: Brandão, Julliany Sales
• Data de Publicação: 2009
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UERJ
• Texto Completo: http://www.bdtd.uerj.br/handle/1/13806
• topic: Cutting stock problem; Genetic algorithms; Combinatorial optimization; Operational research; One-dimensional cutting problem; Setup; Problema do corte de estoque; Algoritmos genéticos; Otimização combinatória; Pesquisa operacional; Problema de corte unidimensional; Setup; CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO::PESQUISA OPERACIONAL

This dissertation presents the application of the one new approach using Genetic Algorithm in solving One-Dimensional Cutting Problems, in order to minimize two objectives, usually conflicting, the number of processed objects and setup, simultaneously. The cutting problem basically consists in finding the best way to obtain parts of distinct sizes (items) from the cutting of larger parts (objects) with the purpose of minimizing an specific cost or maximizing the profit. The disposition of the items on the object for the making of cuts during its production is called the cutting pattern. The setup is the machine's preparation time. The model problem, the objective function, the method denominated SingleGA and the steps used to solve the problem are also presented. The obtained results of the SingleGA are compared to the following methods: SHP, Kombi234, ANLP300 and Symbio, found in literature, verifying its capacity to find feasible and competitive solutions. The computational results show that the proposed method, which only uses a genetic algorithm to solve these two objectives inversely related, provides good results.