A Novel Immune-PSO Algorithm for Job Shop Scheduling

摘要：

The job shop scheduling problem (JSSP) is one of the most difficult problems, as it is classified as an NP-complete one. Particle Swarm Optimization, a nature-inspired evolutionary algorithm, has been successful in solving a wide range of real-value optimization problems. However, little attempts have been made to extend it to discrete problems. In this paper, a new particle swarm optimization method based on the clonal selection algorithm is proposed to avoid premature convergence and guarantee the diversity of the population. Experimental results indicate that the proposed algorithm is highly competitive, being able to produce better solutions than GA and CLONALG in several cases, and is a viable alternative for solving efficiently job shop scheduling problem.

关键词： Artificial immune system Clonal selection algorithm PSO Job shop scheduling problem

作者: HONG Lu YANG Jing

作者单位: Department of Electronic Engineering,Huaihai Institute of Technology,Lianyungang,China College of Electric Engineering,Guizhou University,Guiyang,China

会议类型: 国际会议

会议名称: 2010 International Conference on Material and Manufacturing Technology(2010材料与制造技术国际会议 ICMMT2010)

会议地点: 重庆

会议语种:英文

页码: 261-265

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）