Pareto-optimal solutions for multi-objective production scheduling problems

被引：0
|
作者：
Bagchi, TP [1 ]
机构：
[1] Indian Inst Technol, Kanpur 208016, Uttar Pradesh, India
来源：
EVOLUTIONARY MULTI-CRITERION OPTIMIZATION, PROCEEDINGS | 2001年 / 1993卷
关键词：
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper adapts metaheuristic methods to develop Pareto optimal solutions to multi-criteria production scheduling problems, Approach is inspired by enhanced versions of genetic algorithms. Method first extends the Nondominated Sorting Genetic Algorithm (NSGA), a method recently proposed to produce Pareto-optimal solutions to numerical multi-objective problems. Multi-criteria flowshop scheduling is addressed next. Multi-criteria job shop scheduling is subsequently examined. Lastly the multi-criteria open shop problem is solved. Final solutions to each are Pareto optimal. The paper concludes with a statistical comparison of the performance of the basic NSGA to NSGA augmented by elitist selection.
引用
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页码：458 / 471
页数：14
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