An Improvement Diploid Genetic Algorithm for Job-shop Scheduling Problem

摘要：

Due to the complexity of JSP, there have some improvement. This paper brings up an improvement diploid genetic algorithm. This algorithm is based on the research which comes from GA. This method uses diploid dominant and recessive operation to inherit and retain the excellent individual genes. With the operation method of using convergence and dissimilation in MEC, the direction of evolution has been improved. The operation of dissimilation construct competes in different populations and the global research. This method improves the algorithm of total convergence and ability of overall research. The improvement algorithm overcomes the prematurity and the poor results of average fitness and genetic algorithm. The results of effectiveness have been shown in simulation experiment by using this algorithm.

作者: Chen GUO Ming HUANG Xu LIANG

作者单位: Software Technology Institute, Dalian Jiaotong University, Dalian, China

会议类型: 国际会议

会议名称: 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management(2011 IEEE 第十八届工业工程与工程管理国际会议 IEEM2011)

会议地点: 长春

会议语种:英文

页码: 36-38

在线出版日期: 2011-09-03（万方平台首次上网日期，不代表论文的发表时间）