Genetic algorithm approach to multi-objective scheduling problem in plastics forming plant
Hisashi Tamaki, Mukai Tomohiro, Kenji Kawakami, Mituhiko Araki · 1998
In this paper, a method of applying genetic algorithms (GAs) to multi-objective scheduling problems is proposed. The key points are (1) an alphabetical representation (i.e., genotype) of feasible schedules (i.e., phenotype), and (2) a reproduction operator of GAs which combines the parallel selection with the Pareto reservation strategy. In the paper, through computational experiments, it is shown that not only one of the Pareto-optimal schedules of a problem but a set of such solutions can be obtained by a single run of the proposed method.