西南交通大学学报（英文版）2006，Vol.14Issue(3)：223-227,5.
Improved Genetic Algorithm for Job-Shop Scheduling
Improved Genetic Algorithm for Job-Shop Scheduling
Cheng Rong 1Chen Youping 2Li Zhigang1
作者信息
- 1. School of Materials Science & Engineering, Huazhong University of Science and Technology, Wuhan 430070, China
- 2. College of Engineering and Technology, Shenzhen University, Sheazhen 518060, China
- 折叠
摘要
Abstract
This paper presents a new genetic algorithm for job-shop scheduling problem. Based on schema theorem and building block hypothesis, a new crossover is proposed. By selecting short, low-order, highly fit schemas for genetic operator, the crossover can maintain a diversity of population without disrupting the characteristics and search the global optimization. Simulation results on famous benchmark problems MT06, MT10 and MT20 coded by Matlab show that our genetic operators are suitable to job-shop scheduling problems and outperform the previous GA-based approaches.关键词
Job-shop scheduling/Genetic algorithm/Schema theorem/Building block hypothesisKey words
Job-shop scheduling/Genetic algorithm/Schema theorem/Building block hypothesis分类
数理科学引用本文复制引用
Cheng Rong,Chen Youping,Li Zhigang..Improved Genetic Algorithm for Job-Shop Scheduling[J].西南交通大学学报（英文版）,2006,14(3):223-227,5.
