Minimizing makespan in Job-shop Scheduling Problem Using an Improved Adaptive Particle Swarm Optimization Algorithm
This paper proposes an improved adaptive particle swarm optimization algorithm (IAPSO) for the minimization of makespan in job shop scheduling problems (JSP). Inspired by hormone modulation mechanism, an adaptive hormonal factor (HF) is designed to be used in the updating equations of particle swarm. Using the HF, each particle of the swarm can adjust its particle position self-adaptively to avoid the premature phenomena and get better solution. Computational experiments demonstrate that the proposed IAPSO reaches high-quality solutions in short computational times. By employing IAPSO, machines can be used more efficiently, which means tasks can be allocated appropriately, production efficiency can be improved, and the production cycle can be shortened efficiently.
Job-shop scheduling problem (JSP) Hormone modulation mechanism Improved adaptive particle swarm optimization algorithm (IAPSO) minimum makespan
Wenbin Gu Dunbing Tang Kun Zheng
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
3201-3205
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）