用遗传算法解决生产线调度Job—Shop问题

在分析国内外各种解决生产线作业调度疸方法的基础上，引出生产线调度Job-Shop问题的数学模型。针对该模型，用遗传算法对其进行优化调度。首先针对优化目标进行染色体编码，定义群体规模，然后设计适应度函数，最后通过选择、交叉、变异等操作，得到目标的全局较优解。本文针对某一工程实例，给出了此调度算法的仿真结果。

The Solving of Job-Shop Scheduling Problem Based on Genetic Algorithm

Based on the analysis of various ways in solving Job-Shop scheduling problems, the mathematical model of Job-Shop problem is introduced. A kind of genetic algorithm is used to solve it in this paper. Firstly, the chromosomes are encoded, and the population size is premised for the optimized goal of Job-Shop problem, which are the keys of the method. Secondly, the fitness function is designed. After using selection, crossover and mutation operator, and then elitist strategy to prevent the premature convergence, a best or satisfactory scheduling path can be found. The executing results using the presented algorithms in certain project case are shown in the paper.