Abstract—This paper presents a hybrid approach by a combination of particle swarm optimization (PSO) and parallel simulated annealing (PSA) algorithms. PSO is a population based heuristic method that sometimes traps in local maximum. To cope with this problem, we utilized simulated annealing. However, since SA is extremely greedy regarding the number of iterations, a parallel approach can be performed to decrease the total iterations. In this article, we utilized discrete PSO to achieve a good local maximum. Then parallel SA (PSA) is employed to escape from this locality. Study on the n-queens problem shows that PSO-PSA is promising in solving constraint satisfaction problems.

Index Terms—Constraint satisfaction, parallel simulated annealing, particle swarm optimization.

The authors were with Shahid Chamran University of Ahvaz, Iran (e-mail: pouryajafarzadeh@gmail.com, vahid.msaffarzadeh@gmail.com).

 

Cite:Pourya Jafarzadeh and Vahid Mohammadi Saffarzadeh, "A Hybrid Approach Using Particle Swarm Optimization and Parallel Simulated Annealing: A Case Study of n-Queens Problem," International Journal of Computer and Electrical Engineering vol. 6, no.3, pp. 231-235, 2014.