基于自适应免疫遗传算法的IPPS问题研究  

Research of IPPS Based on Self-adaptive Immune Genetic Algorithm

作　　者：刘琦铀[1] 张成科[1] 李铁克[2] 

机构地区：[1]广东工业大学经贸学院,广东广州510000 [2]北京科技大学东凌经济管理学院,北京100083

出　　处：《工业工程与管理》2015年第2期46-53,共8页Industrial Engineering and Management

基　　金：国家自然科学基金资助项目(71171061);教育部博士学科点专项科研基金资助项目(20100006110006);中央高校基本科研业务费专项资金资助(FRF-SD-12-011B)

摘　　要：针对工艺规划与调度集成(Integration of Process Planning and Scheduling,IPPS)的多目标优化问题,将遗传算法基本理论与免疫应答机理相结合,并引入IPPS问题研究中,构造了融遗传算法和免疫机理为一体的自适应免疫遗传算法(Self-adaptive Immune Genetic Algorithm,SIGA)。该算法以遗传算法为主体并加入免疫算子,通过免疫系统的自适应、免疫识别、学习、记忆、激增和抑制等复杂的信息处理机理,有效地解决了规模大、约束多、目标函数非单一的IPPS问题。最后以实例进行仿真优化,验证了模型算法的正确性和有效性。To solve the integration of process planning and scheduling（IPPS）with multiple obieets,a Self-adaptive Immune Genetic Algorithm（SIGA）, combining the basic theory of the genetic algorithm and immune response mechanism, is introduced in the research of IPPS. With the genetic algorithm as its main body, the immune operator is added in. Through complicated information processing mechanism including self-adaptiveness, immune recognition, learning, memorizing,proliferation and suppression of the immune system, the IPPS problems with large scale, multiple constraints and objects could be resolved effectively. Finally, simulation and optimization are made on real cases to verify the correctness and validity of the algorithm.

关 键 词：工艺规划 自适应 生物免疫 遗传算法 多目标 

分 类 号：TP278[自动化与计算机技术—检测技术与自动化装置]