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
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;
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.2009.5303645
