Multi-population interactive coevolutionary algorithm for flexible job shop scheduling problems

作者：Xing, Li Ning^*; Chen, Ying Wu; Yang, Ke Wei

来源：Computational Optimization and Applications, 2011, 48(1): 139-155.

DOI：10.1007/s10589-009-9244-7

• Combinatorial optimization
• Flexible job shop scheduling
• Genetic algorithm
• Ant colony optimization
• Multi-population
• Interactive
• Coevolutionary

In this paper, it proposes a multi-population interactive coevolutionary algorithm for the flexible job shop scheduling problems. In the proposed algorithm, both the ant colony optimization and genetic algorithm with different configurations were applied to evolve each population independently. By the interaction, competition and sharing mechanism among populations, the computing resource is utilized more efficiently, and the quality of populations is improved effectively. The performance of our proposed approach was evaluated by a lot of benchmark instances taken from literature. The experimental results have shown that the proposed algorithm is a feasible and effective approach for the flexible job shop scheduling problem.

• 出版日期2011-1
• 单位中国人民解放军国防科学技术大学