Title :
Swarm Refinement PSO for Solving N-queens Problem
Author :
Wang, Yuh-Rau ; Lin, Hsieh-Liang ; Yang, Ling
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., St. John´´s Univ., Taipei, Taiwan
Abstract :
In this paper, we introduce a hybrid approach of particle swarm optimization (PSO) for solving n-queens problem. Since the solution of n-queens problem is to create a set of non-conflict queens, we propose a swarm refinement technique to reduce conflicts in main swam and then locate final solutions by swapping permutations. The swarm refinement PSO (SR-PSO) performs much faster and more accurate than the original discrete PSO.
Keywords :
particle swarm optimisation; refinement calculus; SR-PSO; hybrid particle swarm optimization approach; n-queens problem solving; nonconflict queens; original discrete PSO; swapping permutations; swarm refinement PSO; swarm refinement technique; Algorithm design and analysis; Computer science; Educational institutions; Genetic algorithms; Indexes; Particle swarm optimization; Sociology; Particle swarm optimization (PSO); genetic algorithm (GA); n-queens problem; swarm refinement;
Conference_Titel :
Innovations in Bio-Inspired Computing and Applications (IBICA), 2012 Third International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4673-2838-8
DOI :
10.1109/IBICA.2012.43
