DocumentCode
2143329
Title
Multi-Objective Optimization for Dynamic Job-Shop Scheduling in Manufacturing Grid
Author
Gao, Yang ; Ding, Yusi ; Zhang, Hongyu
Author_Institution
Sch. of Bus., Central South Univ., Changsha, China
fYear
2009
fDate
20-22 Sept. 2009
Firstpage
1
Lastpage
4
Abstract
This paper proposes a layered hybrid ant colony and genetic algorithm to solve the multi-objective optimization of dynamic job-shop scheduling problem in manufacturing grid. This algorithm is constructed in a layered structure, where the out layer uses ant colony algorithm to select the machine and the inner layer uses genetic algorithm with neighborhood search to optimize the job scheduling. We use a test example to show the feasibility and efficiency of the algorithm.
Keywords
genetic algorithms; grid computing; job shop scheduling; search problems; dynamic job shop scheduling; genetic algorithm; hybrid ant colony algorithm; manufacturing grid; multiobjective optimization; neighborhood searching; Ant colony optimization; Dynamic scheduling; Genetic algorithms; Internet; Job shop scheduling; Manufacturing processes; Production; Pulp manufacturing; Scheduling algorithm; 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.2009.5303645
Filename
5303645
Link To Document