An Improved Particle Swarm Optimization Algorithm and Its Application to a Class of JSP Problem

摘要：

In this paper, we analyze the special job shop scheduling problem (JSP) of actual production system in large-scale structure workshops. With regard to this kind of JSP problem, two novel mathematical models (deterministic model and stochastic model) are proposed. In addition, Particle Swarm Optimization (PSO) algorithm is used in the paper because of its high efficiency, and Binary PSO algorithm is improved for solving this special scheduling problem, i.e. how to arrange m workers to process n jobs. The results obtained from the simulation study demonstrate that using this heuristics method to solve mathematical models can reach optimal or near-optimal solutions efficiently, and can be widely used in many actual manufactories’ workshops.

作者: Kun Fan Ren-qian Zhang Guoping Xia

作者单位: Beihang University, Beijing, 100083, PR China.

会议类型: 国际会议

会议名称: 2007年IEEE灰色系统与智能服务国际会议(2007 IEEE International Conference on Grey Systems and Intelligent Services)

会议地点: 南京

会议语种:英文

在线出版日期: 2007-11-18（万方平台首次上网日期，不代表论文的发表时间）