A Comparative Study of Evolutionary Computation Techniques for the Generalized Assignment Problem
نویسندگان
چکیده
This paper presents a comparative study among default implementations of Genetic Algorithm, Differential Evolution and Particle Swarm Optimization for load balancing, a specific case of the Generalized Assignment Problem (GAP). Differential Evolution was found the best algorithm, and it was further tested with harder GAP instances to determine its best configuration, so as to be applied to other GAP-like problems. Resumo. Este trabalho apresenta um estudo comparativo entre implementações padrão do Algoritmo Genético, Evolução Diferencial e Otimização por Enxame de Partículas no problema de balanceamento de carga, um caso específico do Problema Generalizado de Atribuição (GAP). Neste estudo comparativo, o algoritmo de Evolução Diferencial apresentou o melhor desempenho. Por isso, o algoritmo foi também experimentado em instâncias GAP mais complexas a fim de determinar a sua melhor configuração para execução deste tipo de problema.
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