MEDAL Report 2008006
Parallel Ant Colony Optimization for the Quadratic Assignment Problems with Symmetric Multi Processing
Shigeyoshi Tsutsui  (2008)

Abstract. Recently symmetric multi processing (SMP) has become available at a reasonable cost. In SMP, parallel run can be performed efficiently with less communication overhead among processors. 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. As a base ACO algorithm, we used the cunning Ant System (cAS) which showed promising performance our in previous studies. We evaluated each parallel algorithm with a condition that the run time for each parallel algorithm and the base seaquential algorithm are the same. The results suggest that using the master-slave model with increased iteration of ACO algorithms is promising in solving QAPs.

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Missouri Estimation of Distribution Algorithms Laboratory
Department of Mathematics and Computer Science
University of Missouri-St. Louis, St. Louis, MO


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