求解FJSP的自适应免疫遗传算法  

Adaptive Immune Genetic Algorithm for Flexible Job-shop Scheduling Problem

作　　者：马佳[1,2] 石刚[1] 高立群[1] 李丹[1] 

机构地区：[1]沈阳航空工业学院经济与管理学院,沈阳110134 [2]东北大学信息科学与工程学院,沈阳110004

出　　处：《系统仿真学报》2009年第12期3609-3613,共5页Journal of System Simulation

基　　金：国家自然科学基金(60274009)

摘　　要：借鉴生物免疫系统的免疫调节机理,提出一种求解柔性作业车间调度问题的自适应免疫遗传算法(AIGA)。该算法在保留基本遗传算法(SGA)随机全局搜索能力的基础上,通过引入免疫算子和种群的自适应调节策略,保持了群体的抗体多样性。实验结果表明,该算法可有效改善基本遗传算法的未成熟收敛和局部搜索能力差的缺点,具有很好的全局收敛能力,能有效解决柔性作业车间调度问题。Based on the immune regulating mechanism of biological immune system, a kind of adaptive immune genetic algorithm （AIGA） was introduced to deal with flexible job-shop scheduling problem. This algorithm not only preserves global research ability of simple genetic algorithm （SGA）, but also adopts the immune operator and adaptive regulation strategy to improve greatly the diversity of antibodies population. Experimental results show that the proposed AIGA can rise above efficiently such difficulties of SGA as precocious convergence and poor local search ability and provide well the global converging ability to enhance both global convergency and convergence rate, thus solving effectively the FJSP problem.

关 键 词：柔性作业车间调度 免疫遗传算法 免疫算子 自适应策略 疫苗 

分 类 号：O224[理学—运筹学与控制论]