Journal of Applied Mathematics
Volume 2012 (2012), Article ID 651310, 20 pages
Research Article

Solving Flexible Job-Shop Scheduling Problem Using Gravitational Search Algorithm and Colored Petri Net

1Department of Computer Engineering, Islamic Azad University, Nowshahr Branch, Nowshahr 4817713655, Iran
2Department of Computer Engineering, Islamic Azad University, Sari Branch, Sari, Iran
3Department of Computer Engineering, Mazandaran University of Science and Technology, Iran

Received 31 December 2011; Revised 6 April 2012; Accepted 14 April 2012

Academic Editor: Nazim I. Mahmudov

Copyright © 2012 Behnam Barzegar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN) that is based on gravitational search algorithm (GSA). In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.