Parallel Ant Colony Optimization for the Quadratic Assignment Problems with Symmetric Multi Processing
Recently symmetric multi processing (SMP) has become available at a reasonable cost. In this paper, we propose several types of parallel ACO algorithms with SMP for solving the quadratic assignment problem (QAP). These models include the master-slave models and the island models. We evaluated each parallel algorithm with a condition that the run time for each parallel algorithm and the base sequential algorithm are the same. The results suggest that using the master-slave model with increased iteration of ACO algorithms is promising in solving QAPs.
KeywordsLocal Search Parallel Algorithm Parallel Model Quadratic Assignment Problem Island Model
Unable to display preview. Download preview PDF.
- 1.Stützle, T.: Parallelization strategies for ant colony optimization. In: 5th International Conf. on Parallel Problem Solving for Nature (PPSN-V), pp. 722–731 (1998)Google Scholar
- 2.Manfrin, M., Birattari, M., Stützle, T., Dorigo, M.: Parallel ant colony optimization for the traveling salesman problems. In: Ant Colony Optimization and Swarm Intelligence, 5th International Workshop, ANTS 2006, pp. 224–234 (2006)Google Scholar
- 3.Tsutsui, S.: cAS: Ant colony optimization with cunning ants. In: Proc. of the 9th Int. Conf. on Parallel Problem Solving from Nature (PPSN IX), pp. 162–171 (2006)Google Scholar
- 6.Benkner, S., Doerner, K., Hartl, R., Kiechle, G., Lucka, M.: Communication strategies for parallel cooperative ant colony optimization on clusters and grids. In: Complimentary Proc. of PARA 2004 Workshop on State-of-the-art in Scientific Computing, pp. 3–12 (2005)Google Scholar
- 7.Bullnheimer, B., Kotsis, G., Strauss, C.: Parallelization strategies for the ant system. High Performance Algorithms and Software in Nonlinear Optimization, 87–100 (1998)Google Scholar
- 9.Lv, Q., Xia, X., Qian, P.: A parallel aco approach based on one pheromone matrix. In: Ant Colony Optimization and Swarm Intelligence, 5th International Workshop, ANT 2006, pp. 332–339 (2006)Google Scholar
- 12.Dorigo, M., Maniezzo, V., Colorni, A.: The ant system: Optimization by a colony of cooperating agents. IEEE Trans. on SMC-Part B 26(1), 29–41 (1996)Google Scholar
- 13.Taillard, É.D.: The robust taboo search code, http://mistic.heig-vd.ch/taillard/
- 15.QAPLIB – A Quadratic Assignment Problem Library, http://www.seas.upenn.edu/qaplib/