Solving fuzzy job-shop scheduling problem by genetic algorithm

摘要：

In this study, we propose a genetic algorithm for solving the job-shop scheduling problem with fuzzy makespan. The solution in the proposed algorithm is represented by a string of discrete values. The crossover and mutation operators are designed to make the proposed algorithm with high quality exploration and exploitation capability. Experimental results on several random generated cases verified the efficiency and effectiveness of the proposed algorithm.

关键词： Fuzzy processing time Job shop scheduling problem Genetic algorithm.

作者: Junqing Li Shengxian Xie Tao Sun Yuting Wang Huaqing Yang

作者单位: School of Computer, LiaochengUniversity, Liaocheng, Shandong, 252059, China School of Computer, LiaochengUniversity, Liaocheng, Shandong, 252059, China.

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 3255-3259

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）