基于免疫遗传算法的车间调度问题的研究

根据生命科学中免疫系统的信息处理机制,在一般遗传算法的基础上,将免疫计算和改进的遗传算法(预防近亲结合的多重交叉策略)相结合,建立了一种用于车间调度的免疫遗传算法,通过接种疫苗提高抗体的适应度,通过免疫选择防止种群的退化。针对作业车间调度问题,设计了免疫遗传计算中疫苗的提取和接种方法,即基于加工机器的基因片断抽取疫苗方法和接种方法。通过作业车间调度十个典型标准问题验证,文中所述免疫遗传算法可行,较现有免疫算法、一般遗传算法及一些传统优化设计方法在收敛效率和准确性等方面有很大改进与提高。

Study of Job Shop Scheduling Using Immune Genetic Algorithm

According to the information processing mechanism of an immune system in biotic science,on the basis of simple genetic algorithm,we propose a new immune genetic algorithm for job shop scheduling through combining immune algorithm with improved genetic algorithm(multi-crossover strategy for preventing incest).We raise the fitness of an antibody by vaccination and prevent species degeneration by immune selection.To deal with a job shop scheduling problem,we design the method for extracting and injecting vaccines during immune genetic calculation,which is based on the gene segments processed by a machine.Finally we verify the convergence efficiency and accuracy of the immune genetic algorithm in solving 10 standard job shop scheduling problems.The verification results indicate that it is better than the existing immune algorithm,simple genetic algorithm and some traditional optimal design methods.