Hybrid immune genetic algorithm with neighborhood search operator for the Job Shop Scheduling Problem

Abstract

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.