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A genetic approach to dynamic scheduling for total weighted tardiness problem
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Orientador(es)
Resumo(s)
This paper presents several local search metaheuristics for the problem of scheduling a single
machine to minimise total weighted tardiness. A genetic algorithm for the static single machine total
weighted tardiness problem is presented, and a multistart version named metaGA is proposed. The
obtained computational results permit to conclude about their efficiency and effectiveness.
The resolution of the dynamic single machine total weighted tardiness problem using a scheduling system
based on Genetic Algorithms (GA) is proposed. This approach extends the resolution of static Single Machine Scheduling Problems (SMSP) to dynamic SMSP in which changes can occur continually. A new population generating mechanism for dynamic environments is proposed. This method takes into account dynamic occurrences in a system, and adapts the current modified population into a new regenerated population.
Descrição
Palavras-chave
Scheduling dynamic scheduling metaheuristics genetic algorithms
Contexto Educativo
Citação
Madureira, A., Ramos, C. & Silva, S. C. (1999, December 15-16). A genetic approach to dynamic scheduling for total weighted tardiness problem. In Petley, G., Coddington, A. & Aylett, R. (Eds). Proceedings of the Eighteenth Workshop of the UK Planning and Scheduling Special Interest Group. (pp.100-108). University of Salford, UK.
Editora
University of Salford
Licença CC
Sem licença CC