改进多种群杂交遗传算法在作业车间调度的研究

Multi-population Genetic Algorithm and Improvement In Job Shop Scheduling

通过提出应用最广泛的混合型作业车间的调度问题以及遗传算法的基本原理，并结合生产车间调度问题的特点，对传统单种群遗传算法改进了改进。新遗传算法中加入辅助种群，保证种群的多样性，解决单个种群的遗传算法容易陷入局部收敛而出现早熟的情况。并应用实例对比分析，表明算法在车间调度系统的有效性和合理性。

Presents the most widely used hybrid job shop scheduling problems and the basic principles of genetic algorithms, and for this production features shop scheduling problems, improve the traditional genetic algorithm. Adding new auxiliary popula-tion genetic algorithm to ensure the diversity of population, the genetic algorithm to solve a single easy to fall into the local popu-lation and the premature convergence of circumstances. Analysis and application examples, show that the algorithm is effective and reasonable in the shop scheduling system.