基于粒子群算法的车间作业调度问题

Job shop scheduling problem based on particle swarm optimization

通过对车间调度问题的描述,针对传统算法寻优效率低的弱点,提出了一种基于粒子群算法的车间作业调度问题的解决方案。对粒子群算法的基本原理进行了阐述,并对粒子群算法的编码、参数的选择以及解码进行了研究,以最小化最大流程时间作为评价算法的性能指标,将其用于编程求解典型调度问题。仿真结果表明,粒子群算法在求解车间作业调度的应用上是十分有效的。

Considering the conventional algorithms＇ low efficiency of searching for optimizing in job shop scheduling problems, the job shop scheduling solution is presented based on particle swarm optimization algorithm. In this paper, the basic theory of particle swarm optimization is described, also, the coding and selection of parameters as well as the decoding of PSO are studied. It uses the maximum flow time which being minimized to evaluate performance of the algorithm, and applies it to solve a typical scheduling problem. The simulation results show that PSO applied in solving job-shop scheduling is very effective.