基于改善初始种群的免疫遗传算法优化JSP问题  

An Immune Genetic Algorithm Based on Improving Initial Population for JSP

作　　者：周帅[1] 黄宗南[1] Zhou Shuai;Huang Zongnan

机构地区：[1]上海大学机电工程与自动化学院,上海200072

出　　处：《计量与测试技术》2018年第5期10-12,共3页Metrology & Measurement Technique

摘　　要：合理安排加工任务可以最大化的利用设备。针对单件车间问题采用免疫遗传算法进行求解,设计了具体的初始种群改善方法,将采用能动法和无延迟法生成个体替换随机初始种群中适应度最低的个体的方法融入到初始种群生成过程,提高初始种群质量。通过标准案例测试,与无改善初始种群的算法比较,表明了改善算法的良好求解性能。Reasonable arrangements for processing tasks can maximize the use of equipment. Aiming at the single -workshop problem, an immune genetic algorithm was used to solve the problem. A specific initial population improvement method was designed. The method of generating individuals to replace the individuals of lowest fitness in random initial populations by the active method and the no delay method was integrated into the initial population generation process, to improve initial population quality. rithm without improvement of the initial population, the Through the standard case test, compared with the algo- better solution performance of the improved algorithm is shown.

关 键 词：单件车间调度 免疫遗传算法 初始种群 能动法 无延迟法 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]