国际设备工程与管理（英文版）2004，Vol.9Issue(2)：91-96,6.
A Grafted Genetic Algorithm for the Job-Shop Scheduling Problem
A Grafted Genetic Algorithm for the Job-Shop Scheduling Problem
摘要
Abstract
The standard genetic algorithm has limitations of a low convergence rate and premature convergence in solving the job-shop scheduling problem.To overcome these limitations,this paper presents a new improved hybrid genetic algorithm on the basis of the idea of graft in botany.Through the introduction of a grafted population and crossover probability matrix,this algorithm accelerates the convergence rate greatly and also increases the ability to fight premature convergence.Finally,the approach is tested on a set of standard instances taken from the literature and compared with other approaches.The computation results validate the effectiveness of the proposed algorithm.关键词
grafted genetic algorithm/job-shop scheduling problem/premature convergence/hy brid optimization strategyKey words
grafted genetic algorithm/job-shop scheduling problem/premature convergence/hy brid optimization strategy分类
机械制造引用本文复制引用
LI Xiang-jun,WANG Shu-zhen,XU Guo-hua..A Grafted Genetic Algorithm for the Job-Shop Scheduling Problem[J].国际设备工程与管理（英文版）,2004,9(2):91-96,6.基金项目
This paper is supported by the General Ministry of Armed Forces under Grant No.QB1014 and by the Scientific Research Foundation of Xi'an University of Arts and Science under Grant No.200131. （）
