Abstract：To maximize the utilization of bottleneck workstation and achieve a high throughput with a reasonable cycle time, an improved multiobjective particle swarm optimization algorithm (IMOPSO) was proposed with an objective function to minimize the total flow time and the weighed average time of earliness and tardiness. The performance of the bottleneck workstation was analyzed. A multiobjective optimization model was built based on the mapping requirements of rapid productions as total flow time and just in time delivery as weighed average time of earliness and tardiness of the bottleneck workstation. An IMOPSO algorithm was established for the scheduling of bottleneck workstation by improving an update mechanism of velocity and position with a crossover operation to the particle falling into local optimum. Based on stability, quality, convergence rate and run time, the simulation experiments were performed to evaluate the proposed algorithm under the conditions of different job scales. The results show that the proposed algorithm is valid and feasible to improve the scheduling performance of bottleneck workstation.
周炳海, 胡新宇, 孙超. 基于改进型多目标粒子群算法的晶圆制造系统瓶颈工作站调度[J]. 江苏大学学报（自然科学版）, 2014, 35(1): 63-68.
ZHOU Bing-Hai, HU Xin-Yu, SUN Chao. Scheduling of bottleneck workstation in wafer fabrication systems based on improved multiobjective particle swarm optimization algorithm[J]. Journal of Jiangsu University(Natural Science Eidtion)
, 2014, 35(1): 63-68.
2014, Vol. 35 
