Improved Genetic Algorithm for Solving the Fuzzy Multiobjective Job shop problem
This paper studies the influence of the encoding and decoding on the result of the Job Shop problem under E/T indicators and improve the coding methods to make the optimal object span in order to adapt to different delivery windows earliness/tardiness scheduling problem. In this paper, The trapezoidal fuzzy number which has more representation as flexible operating processing time under fuzzy environment was used. Multi-attribute decision making method based on possibility was used. In this way it can reduce the intermediate process, avoid the loss of information, and enhance the effectiveness of fuzzy evaluation. Simulation results verify the effectiveness of the algorithm.
Multi-attribute Decision Making Fuzzy Multiobjective Genetic Algorithm Job Shop Scheduling
He-ping WANG Lei SHI
Anhui University of Technology,Maanshan Anhui China 243002 Anhui University of Technology, Maanshan Anhui China 243002
国际会议
厦门
英文
1542-1545
2010-10-29（万方平台首次上网日期，不代表论文的发表时间）