单件车间调度问题的改进型病毒进化遗传算法  

Improved virus evolutionary genetic algorithm for job-shop scheduling problem

作　　者：刘胜辉[1] 张淑丽[1] 王波[1] 滕春贤[1] 

机构地区：[1]哈尔滨理工大学软件学院,黑龙江哈尔滨150080

出　　处：《电机与控制学报》2008年第2期234-238,共5页Electric Machines and Control

基　　金：国家自然科学基金资助项目(69984002)

摘　　要：针对单件车间调度问题,设计了一种改进型病毒进化遗传算法IVEGA。为提高局部搜索能力,有效地避免丢失优秀解,缩小搜索空间,算法在主个体遗传过程和病毒感染过程中分别加入了主群体知识库和病毒群体知识库,并引入学习机制。通过对11个经典的Benchmarks问题进行了求解,结果表明了IVEGA的相对偏差为1.66%。An improved virus evolutionary genetic algorithm IVEGA （improved virus evolutionary genetic algorithm） was designed for job-shop scheduling problem, In the algorithm, a knowledge-base of host chromosome into the genetic process and another knowledge-base of virus chromosome into the virus infect process were added and learning theories were introduced to increase local search ability, avoid tile loss of the excellent solution and shrink the searching space. It showes the relative deviation of IVEGA is 1.66% in solvin~ eleven classical Benchmarks problems.

关 键 词：单件车间调度 病毒进化遗传算法 学习机制 知识库 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]