Serviços Personalizados
Journal
Artigo
Indicadores
- Citado por SciELO
- Acessos
Links relacionados
- Citado por Google
- Similares em SciELO
- Similares em Google
Compartilhar
DYNA
versão impressa ISSN 0012-7353versão On-line ISSN 2346-2183
Resumo
FRUTOS, MARIANO e TOHME, FERNANDO. EVOLUTIONARY MULTI-OBJECTIVE SCHEDULING PROCEDURES IN NON-STANDARDIZED PRODUCTION PROCESSES. Dyna rev.fac.nac.minas [online]. 2012, vol.79, n.172, pp.101-107. ISSN 0012-7353.
Scheduling problems can be seen as multi-objective optimization problems (MOPs), involving the simultaneous satisfaction of several goals related to the optimal design, coordination, and management of tasks. The complexity of the goal functions and of the combinatorial methods used to find analytical solutions to them is quite high. The search for solutions (Pareto-optima) is better served by the use of genetic algorithms (GAs). In this paper, we analyze the performance of the non-dominated sorting genetic algorithm II (NSGAII), strength Pareto evolutionary algorithm II (SPEAII), and their predecessors, NSGA and SPEA, when these are devoted to scheduling tasks in non-standardized production activities.
Palavras-chave : Job-shop scheduling; multi-objective optimization; Pareto frontier; memetic algorithm; local search.