病毒遗传算法在非流水作业调度中的应用  

Application of Virus Co-Evolution Genetic Algorithm in Solving Non-Flow shop Scheduling

作　　者：杨民[1] 

机构地区：[1]海军装备部舰船办,北京100071

出　　处：《计算机与数字工程》2014年第5期775-778,共4页Computer & Digital Engineering

摘　　要：非流水作业调度是相对流水作业调度的一种调度问题,与流水调度作业相比,该模型拥有更大的解空间,用解析方法求解是不可能的。本文基于病毒遗传算法框架设计了一种基于任务工作序列和机器分配模式的主个体编码形式的遗传算法,并对机器分配模式进行病毒操作,进而增强遗传过程的局部搜索能力。试验表明,该算法运行有效,在计算效果上比基本遗传算法具有明显优势。Non-flow shop scheduling problem which is relative to flow shop scheduling, contrasting the flow shop scheduling problem, this problem has larger neighbor space, and it can＇t be solved in mathematics method. We propose the genetic algorithm with encoding task sequence and machine distribution schema based on Virus Co-Evolution Genetic Algo- rithm, which virus operator being used in machine distribution schema to improve the local search capacity of genetic process. The experiment shows that the algorithm can solve non-flow shop scheduling well and the performance of the algorithm is better than basic genetic algorithm.

关 键 词：非流水作业调度 任务工作序列 机器分配模式 病毒遗传算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]