Research on Parallel Machine Scheduling Based on Genetic Neighborhood Hybrid Algorithm

For the unrelated parallel machine scheduling problem, a scheduling model with the minimum completion time as the optimization goal is established. By combining genetic algorithm and neighborhood search, a genetic-neighbor search alternate hybrid algorithm is designed. The influence of genetic algorithm population number and evolutionary algebra on the optimal solution is discussed when solving the unrelated parallel machine scheduling problem. Finally, the proposed hybrid algorithm is used to solve parallel machine scheduling problems of different scales, and compared with a single genetic algorithm to verify the effectiveness and feasibility of the proposed algorithm.