A Petri net-based particle swarm optimization approach for scheduling deadlock-prone flexible manufacturing systems
- 323 Downloads
This paper proposes an effective hybrid particle swarm optimization (HPSO) algorithm to solve the deadlock-free scheduling problem of flexible manufacturing systems (FMSs) that are characterized with lot sizes, resource capacities, and routing flexibility. Based on the timed Petri net model of FMS, a random-key based solution representation is designed to encode the routing and sequencing information of a schedule into one particle. For the existence of deadlocks, most of the particles cannot be directly decoded to a feasible schedule. Therefore, a deadlock controller is applied in the decoding scheme to amend deadlock-prone schedules into feasible ones. Moreover, two improvement strategies, the particle normalization and the simulated annealing based local search, are designed and incorporated into particle swarm optimization algorithm to enhance the searching ability. The proposed HPSO is tested on a set of FMS examples, showing its superiority over existing algorithms in terms of both solution quality and robustness.
KeywordsFlexible manufacturing systems Deadlock Scheduling Timed Petri nets Particle swarm optimization Simulated annealing
This work was supported in part by the National Natural Science Foundation of China under Grants 61473216 and 61573278.
- Dashora, Y., Kumar, S., Tiwari, M. K., & Newman, S. T. (2007). Deadlock-free scheduling of an automated manufacturing system using an enhanced colored time resource Petri-net model-based evolutionary endosymbiotic learning automata approach. International Journal of Flexible Manufacturing Systems, 19(4), 486–515.CrossRefGoogle Scholar
- Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In IEEE international conference on neural networks (pp. 1942–1948). Perth: IEEE.Google Scholar
- Moslehi, G., & Mahnam, M. (2011). A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search. International Journal of Production Economics, 129(1), 14–22.Google Scholar
- Pinedo, M. L. (2008). Scheduling: Theory, algorithms, and systems (3rd ed.). New York: Springer.Google Scholar
- Xu, G., & Wu, Z. M. (2002). Deadlock-free scheduling method using Petri net model analysis and GA search. In IEEE international conference on control applications (pp. 1153–1158). Glasgow: IEEE.Google Scholar
- Yoon, H. J., & Lee, D. Y. (2004). Deadlock-free scheduling of photolithography equipment in semiconductor fabrication. IEEE Transactions on Semiconductor Manufacturing, 17(1), 42–54.Google Scholar