A hybrid genetic algorithm for job shop scheduling problem to minimize makespan

被引：0
|
作者：
Liu, Lin [1 ]
Xi, Yugeng [1 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, 800 Dongchuan Rd, Shanghai 200240, Peoples R China
来源：
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
基金：
美国国家科学基金会;
关键词：
hybrid genetic algorithm; job shop scheduling; hybrid scheduler;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A hybrid genetic algorithm is presented for the job shop scheduling problem. The chromosome representation is based on random keys. A chromosome includes genes representing the relative priorities of all operations and genes determining the idle time permitted on a machine before processing an operation. The SPV (smallest position value) rule is used to convert a real number vector to a job repetition representation. Then the schedule is constructed using the hybrid scheduler that introduces parameters to control the scope of search space. Finally, a neighborhood-based local search is used to improve the solution quality. The experimental results on the well-known benchmark instances show the proposed algorithm is very effective and competitive with other methods in literatures.
引用
收藏
页码：3709 / +
页数：2
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