• CN：11-2187/TH
• ISSN：0577-6686

›› 2012, Vol. 48 ›› Issue (14): 177-182.

• 论文 •

基于激素调节机制改进型自适应粒子群算法在置换流水车间调度中的应用研究

1. 南京航空航天大学机电学院;河海大学机电学院
• 发布日期:2012-07-20

Research on Permutation Flow-shop Scheduling Problem Based on Improved Adaptive Particle Swarm Optimization Algorithm with Hormone Modulation Mechanism

GU Wenbin;TANG Dunbing;ZHENG Kun;BAI Shuaifu;PEI Wenxiang

1. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics College of Mechanical and Electrical Engineering, Hohai University
• Published:2012-07-20

Abstract: An improved adaptive particle swarm optimization algorithm (IAPSO), which is inspired from hormone modulation mechanism, is used to minimize the maximal makespan of the permutation flow-shop scheduling problem (FSSP). The initial best position of each particle is no longer the randomly generated initial position of each particle; it is converted from the sequence of jobs, which is generated by greedy randomized adaptive search based on heuristics. Inspired from hormone modulation mechanism, the hormonal regular factor (HF) is used to modify the updating equations of particle swarm, which is based on the information of the particles around the single particle. it improves the flying function of the particle swarm in order to obtain better searching efficiency and searching quality. The simulation results based on benchmarks demonstrate its feasibility and effectiveness.