Application of Job Shop Based on Immune Genetic Algorithm
Job Shop scheduling problem.as an important part of computer integrated manufacturing system engineering, is a classic NP-hard combinatorial optimization problem and has vital effect on production management and control system. In this paper, base on biological immune systems antigen recognition, maintaining the diversity of antibodies and other features, a proposed improved genetic algorithm-the immune genetic algorithm is put forward, the algorithm will introduce the thinking of biological systems immune to the genetic algorithm, namely in use of first immune knowledge it structures inspection operator. By vaccination and immune selection, it not only retains the best individual groups but also ensures the diversity of individuals, thus avoiding the premature convergence of evolutionary search and improving convergence speed, meantime, an improved immune genetic algorithm, and adopting timely dynamic vaccination and the shut down criteria are given. Simulation results show that the algorithm is effective.
Genetic Algorithm immune job shop NP-hard hypermutation
Zhang Shu Meng Lei
Mechanical College Shenyang University of Chemical Technology Shenyang, China Software Engineering Shenyang Normal University Shenyang, China
国际会议
2011 International Conference on Database and Data Mining(ICDDM 2011)(2011年数据库和数据挖掘国际会议)
三亚
英文
46-49
2011-03-25（万方平台首次上网日期，不代表论文的发表时间）