.png){kind=icon}
返回
Genetic algorithm integrated with artificial chromosomes for multi-objective flowshop scheduling problems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.amc.2008.05.027.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Recently, a wealthy of research works has been dedicated to the design of effective and efficient genetic algorithms in dealing with multi-objective scheduling problems. In this paper, an artificial chromosome generating mechanism is designed to reserve patterns of genes in elite chromosomes and to find possible better solutions. The artificial chromosome generating mechanism is embedded in simple genetic algorithm (SGA) and the non-dominated sorting genetic algorithm (NSGA-II) to solve single-objective and multiobjective flowshop-scheduling problems, respectively. The single-objective problems are to minimize the makespan while the multi-objective scheduling problems are to minimize the makespan and the maximum tardiness. Extensive numerical studies are conducted and the results indicate that artificial chromosomes embedded with SGA and NSGAII are able to further speed up the convergence of the genetic algorithm and improve the solution quality. This promising result may be of interests to industrial practitioners and academic researchers in the field of evolutionary algorithm or machine scheduling. (C) 2008 Elsevier Inc. All rights reserved.
Keyword:
Genetic algorithm
Flowshop scheduling
Makespan
Maximum tardiness
NSGA II
期刊
IF:
3.4
论文数:
2.3W
被引数:
3.3W
机构
引用论文
An effective hybrid genetic algorithm for flow shop scheduling with limited buffers具有有限缓冲区的流水车间调度的有效混合遗传算法
.png){kind=icon}
PREAI
分享收藏
查看更多内容