Production Logistics Scheduling Optimization Based on Improved Multi-Colony

被引：0
|
作者：
Liu Beilin [1 ]
Ma Li [1 ]
机构：
[1] Harbin Univ Commerce, Sch Management, Harbin 150070, Peoples R China
来源：
PROCEEDINGS OF THE 29TH CHINESE CONTROL CONFERENCE | 2010年
关键词：
Multi-Colony Diploid Genetic Algorithm; Genetic Algorithm; Production Logistics Scheduling Optimization; JOB-SHOP PROBLEM; GENETIC ALGORITHM;
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：
Improved Multi-Colony Diploid Genetic Algorithm (IMCDGA) is studied in order to apply the scheduling theory to the production practice. Aimed at production logistics scheduling optimization for agile manufacturing, a job-shop dynamic scheduling model based on IMCDGA is proposed. Finally, the method mentioned above is applied to solve the scheduling optimization of Shanghai Volksvagen, Automobile Co. Ltd., and the most optimal scheduling can be attained. The simulation results demonstrate that the Improved Multi-Colony Diploid Genetic Algorithm is feasible and effective for production logistics scheduling optimization.
引用
收藏
页码：1753 / 1756
页数：4
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