Scheduling for the Flexible Job-Shop Problem Based on Genetic Algorithm(GA)

摘要：

In this paper, we analyze the characteristics of the flexible job-shop scheduling problem(FJSP). A novel genetic algorithm is elaborated to solve the FJSP. An improved chromosome representation is used to conveniently represent a solution of the FJSP. Initial population is generated randomly. The relevant selection, crossover and mutation operation is also designed. It jumped from the local optimal solution, and the search area of solution is improved. Finally, the algorithm is tested on instances of 4 jobs and 6 machines. Computational results prove the proposed genetic algorithm effective for solving the FJSP.

关键词： Job-shop Scheduling Genetic algorithms Selection Crossover Mutation

作者: ShunCheng Fan JinFeng Wang

作者单位: School of Mechanical Engineering Hebei University of Technology Tianjin, China

会议类型: 国际会议

会议名称: 2011 International Conference on Advanced Materials and Engineering Materials(2011先进材料与工程材料国际会议 ICAMEM 2011)

会议地点: 沈阳

会议语种:英文

页码: 616-619

在线出版日期: 2011-11-22（万方平台首次上网日期，不代表论文的发表时间）