基于改进遗传算法的分批调度研究

Research of Batch Scheduling Based on Improved Genetic Algorithm

针对分批调度的批量划分和排序优化问题,提出两段染色体编码方式,分别描述工序信息和批量信息.提出舍弃比率概念来优化种群初始化过程.采用自适应交叉算子和变异算子,以双种群协同进化方式对遗传算法进行改进.以文献数据为例仿真测试了改进遗传算法的有效性,对于复杂的分批调度问题,改进遗传算法一般能够得到较为满意的解.成功应用分批调度改进遗传算法解决了某公司分批调度问题.

To solve the batch division problem and optimize sequencing problem in the batch scheduling, the text puts forward two section of chromosome coding way to describe process information and batch information, and improves the generic algorithm by way of using discard rate to optimize population initialization process, using adaptive cross operator and adaptive mutation operator and double population co-evolution method. Finally, the validity of improved genetic algorithm is tested by the simulation based on literature data, and the algorithm is successfully applied to solve the batch scheduling problem of a company.