期刊
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS
卷 38, 期 2, 页码 358-368出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMCA.2007.914753
关键词
artificial immune system (AIS); artificial intelligence; job-shop scheduling problem (JSSP); particle swarm optimization (PSO); vaccination
The optimization of job-shop scheduling is very important because of its theoretical and practical significance. In this paper, a computationally effective algorithm of combining PSO with AIS for solving the minimum makespan problem of job-shop scheduling is proposed. In the particle swarm system, a novel concept for the distance and velocity of a particle is presented to pave the way for the job-shop scheduling problem. In the artificial immune system, the models of vaccination and receptor editing are designed to improve the immune performance. The proposed algorithm effectively exploits the capabilities of distributed and parallel computing of swarm intelligence approaches. The algorithm is examined by using a set of benchmark instances with various sizes and levels of hardness and is compared with other approaches reported in some existing literature works. The computational results validate the effectiveness of the proposed approach.
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