Title :
A memetic algorithm for solving flexible Job-Shop Scheduling Problems
Author :
Wenping Ma ; Yi Zuo ; Jiulin Zeng ; Shuang Liang ; Licheng Jiao
Author_Institution :
Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ. of China, Xidian Univ., Xi´an, China
Abstract :
The flexible Job-shop Scheduling Problem (FJSP) is an extension of the classical job-shop scheduling problem (JSP). In this paper, a memetic algorithm (MA) for the FJSP is presented. This MA is a hybrid genetic algorithm which explores the search space and two efficient local searchers to exploit information in the search region. An extensive computational study on 49 benchmark problems shows that the algorithm is effective and robust, with respect to other well-known effective algorithms.
Keywords :
genetic algorithms; job shop scheduling; search problems; FJSP; MA; classical job-shop scheduling problem; flexible job-shop scheduling problems; hybrid genetic algorithm; local searchers; memetic algorithm; search space; Evolutionary computation; flexible job-shop scheduling; memetic algorithm; simulated annealing; tabu search;
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
DOI :
10.1109/CEC.2014.6900332
