DocumentCode
2111612
Title
Research on Job-Shop Problem Based on Multi-Colony Diploid Genetic Algorithm
Author
Huo, Hong ; Yang, Shao-Dong
Author_Institution
Sch. of Manage., Harbin Univ. of Commerce, Harbin, China
fYear
2009
fDate
20-22 Sept. 2009
Firstpage
1
Lastpage
4
Abstract
Multi-Colony Diploid Genetic Algorithm (MCDGA) is studied in order to apply the scheduling theory to the production practice. Aimed at the job-shop dynamic scheduling for agile manufacturing, Job Shop Problem model based on MCDGA is proposed. Finally, the present algorithm is tested on Shanghai Volkswagen, Automobile Co.Ltd. The simulation results show that the proposed algorithm is more effective compared with genetic algorithm.
Keywords
agile manufacturing; automobile industry; genetic algorithms; job shop scheduling; Shanghai Volkswagen Automobile Co Ltd; agile manufacturing; job-shop dynamic scheduling; job-shop problem; multicolony diploid genetic algorithm; scheduling theory; Agile manufacturing; Biological cells; Business; Dynamic scheduling; Entropy; Genetic algorithms; Job production systems; Job shop scheduling; Random variables; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Management and Service Science, 2009. MASS '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4638-4
Electronic_ISBN
978-1-4244-4639-1
Type
conf
DOI
10.1109/ICMSS.2009.5302476
Filename
5302476
Link To Document