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A new contribution for solving dynamic scheduling problems using genetic algorithms
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Orientador(es)
Resumo(s)
Scheduling is an important element of manufacturing systems because it allows to improve the system performance and serves as an overall plan on which system activities are based. The main purpose of this paper isto explore the use of evolutionary computation techniques for solving real world optimisation problems. These classes of problems have additional difficulties for the traditional optimisation techniques. This paper presents a simple and general framework based on Genetic Algorithms to solve dynamic Job-Shop scheduling problems. A new generation of initial individual
and population is proposed. The proposed framework adapts the resolution of the deterministic problem to the non-deterministic one in which changes may occur continually. This takes into account dynamic occurrences in a manufacturing system and adapts the current population.
Descrição
Palavras-chave
Contexto Educativo
Citação
Madureira, A., Ramos, C. & Silva, S. C. (2002, July 24-27). A new contribution for solving dynamic scheduling problems using genetic algorithms [Paper presentation]. Proceedings of the 9th Bellman Continuum International Workshop on Uncertain Systems and Soft Computing, Beijing, China.
Editora
Tsinghua University
Licença CC
Sem licença CC