Future Generation Computer Systems
Parallel ant colonies for the quadratic assignment problem
Future Generation Computer Systems - Special issue on bio-impaired solutions to parallel processing problems
Journal of Heuristics
A parallel implementation of ant colony optimization
Journal of Parallel and Distributed Computing - Problems in parallel and distributed computing: Solutions based on evolutionary paradigms
Parallelization Strategies for Ant Colony Optimization
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Paper: Robust taboo search for the quadratic assignment problem
Parallel Computing
Cunning ant system for quadratic assignment problem with local search and parallelization
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
cAS: ant colony optimization with cunning ants
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Parallel ant colony optimization for the traveling salesman problem
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
A parallel ACO approach based on one pheromone matrix
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Improved assignment with ant colony optimization for multi-target tracking
Expert Systems with Applications: An International Journal
A survey on parallel ant colony optimization
Applied Soft Computing
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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.