关键词: 静态繁殖, 机器学习, 免疫遗传算法, 自适应疫苗<

Abstract: Theories of static multiplication and machine learning were introduced to immune genetic algorithm. The chromosomes’ immunity was boosted and the average fitness of chromosomes was improved by using adaptive vaccine, as a result the loss of optimum solution was avoided, searching space was reduced and evolution speed was increased, then the optimal solution could be achieved earlier. At the same time, the calculation result of the mentioned algorithm was compared with other optimal algorithms in solving classic Job-shop Scheduling Problem.

Key words: static multiplication, machine learning, immune genetic algorithm, adaptive vaccine