A heuristic genetic algorithm for flowshop scheduling

被引：0
|
作者：
Chakraborty, UK [1 ]
Laha, D [1 ]
Chakraborty, P [1 ]
机构：
[1] Univ Missouri, Dept Math & Comp Sci, St Louis, MO 63121 USA
来源：
ITI 2001: PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY INTERFACES | 2001年
关键词：
flowshop scheduling; genetic algorithms; heuristics;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Flowshop scheduling deals with determining the optimum sequence of jobs to be processed on several machines so as to satisfy some scheduling criterion. It is NP-complete. Heuristic algorithms use problem-specific information to yield good working, solution. Genetic algorithms are stochastic, adaptive, general-purpose search heuristics based on concepts of natural evolution. We have developed a new heuristic genetic algorithm (NGA) which combines the good features of both the GA and,heuristic search. The NGA is run on several problems and its performance is compared with that of the conventional genetic algorithm and the well-known NEH heuristic. The NGA is, seen to perform better in almost all instances.
引用
收藏
页码：313 / 318
页数：6
相关论文
共 50 条
12345