基于演化策略算法的作业车间调度优化

提出一种基于工件操作次序的二维实数编码方法，采用演化策略算法求解作业车间调度问题。设计一种基于三点交叉互换的重组算子用于生成子代个体，并采用个体编码基因随机重新生成的方法设计变异算子。实验结果证明，演化策略算法能有效优化作业车间调度问题，与遗传算法和粒子群优化算法相比，其优化性能更好，并且基于三点交叉互换重组算子的演化策略算法的性能好于基于两点交叉和基于四点交叉互换重组算子的演化策略算法。

Job-shop Scheduling Optimization Based on Evolutionary Strategy Algorithm

This paper proposes a two-dimension encoding approach based on the job operation sequence and uses Evolutionary Strategy(ES) algorithm to solve the Job-shop Scheduling Problem(JSP). A kind of recombination operation based on three-point crossover and interchange is used to generate the offspring individuals, and a kind of mutation operation is designed that some gene in the encoding is stochastically generated. Experimental results show that evolutionary strategy algorithm can effectively optimize the JSP and has better performance than genetic algorithm and hybrid particle swarm optimization algorithm. ES algorithm based on three-point crossover and interchange recombination operation has better performance than the recombination operation based on two-point crossover and interchange and the recombination operation based on four-point crossover and interchange.