Adaptive Genetic Algorithm for Hybrid Flow-shop Scheduling

被引：0

作者：

Zhu, Xiao Chun ^{[1
]}

Zhao, Jian Feng ^{[2
]}

Wang, Mu Lan ^{[1
]}

机构：

[1] Nanjing Inst Technol, Jiangsu Key Lab Adv Numer Control Technol, Nanjing, Jiangsu, Peoples R China

[2] Nanyang Tech Inst, School of Automat, Nanjing, Peoples R China

来源：

MATERIALS PROCESSING AND MANUFACTURING III, PTS 1-4 | 2013年 / 753-755卷

关键词：

Adaptive Genetic Algorithm (GA); Hybrid Flow-Shop (HFS); Chromosome; SHOP;

D O I：

10.4028/www.scientific.net/AMR.753-755.2925

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper studies the scheduling problem of Hybrid Flow Shop (HFS) under the objective of minimizing makespan. The corresponding scheduling simulation system is developed in details, which employed a new encoding method so as to guarantee the validity of chromosomes and the convenience of calculation. The corresponding crossover and mutation operators are proposed for optimum sequencing. The simulation results show that the adaptive Genetic Algorithm (GA) is an effective and efficient method for solving HFS Problems.

引用

页码：2925 / +

页数：2

共 8 条

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