A Genetic Algorithm for Job Shop Scheduling with Limited Part-changing Times

被引：0

作者：

Wang, Mingjie ^{[1
]}

Feng, Haodi ^{[1
]}

机构：

[1] Shandong Univ, Sch Comp Sci & Technol, Jinan 250100, Peoples R China

来源：

PROCEEDINGS OF 2012 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2012) | 2012年

关键词：

part-changing times; !text type='JS']JS[!/text]SP; genetic algorithm;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

While many variations of JSSP have been extensively studied, JSSP with limited part-changing times has rarely been explored. However, JSSP with limited part-changing times may find its applications in many manufacturing factories (Part-changing refers to changing some parts of a machine so that the machine can process different types of jobs. Since part-changing is usually carried out by labours, the total part-changing times in a unit time is thus limited). In this paper, we propose a genetic algorithm, MJGA, for this type of JSSP. Since we have seen no early work on this problem, for testing the performance of MJGA, we also propose another two algorithms and compare them with MJGA. Experiments show that MJGA performs better for solving this schedule problem, especially when the instance is getting larger.

引用

页码：1922 / 1926

页数：5