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
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;
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
DOI :
10.1109/ICMSS.2009.5302476
