期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2020
卷号：474
期号：5
页码：1-7
DOI：10.1088/1755-1315/474/5/052093
语种：English
出版社：IOP Publishing
摘要：Immune genetic algorithm has the disadvantage of insufficient local search capability when solving the job-shop scheduling problem, and it is difficult to solve large-scale job-shop scheduling problems well. Aiming at this problem, this paper proposes a hybrid immune genetic algorithm which combines neighborhood search with immune genetic algorithm. After the genetic operation, in addition to the vaccination operation of the poorer individuals in the population, the better individuals will be selected for neighborhood search to improve the local search ability of the algorithm. The neighborhood search operator selects the N5 neighborhood search operator, which can perform a neighborhood search on key paths of high-quality individuals to find a better neighborhood solution. The experimental results show that the hybrid immune genetic algorithm with the neighborhood search method can obtain more standard case optimal solutions.
