Parallel implementations of the ant colony optimization metaheuristic

Abstract

The paper discusses different approaches to parallel implementation of the Ant Colony Optimization metaheuristic. The metaheuristic is applied to the well-known Travelling Salesman Problem. Although the Ant Colony Optimization approach is capable of delivering good quality solutions for the TSP it suffers from two factors: complexity and non-determinism. Overpopulating ants makes the ACO performance more predictable but increasing the number of ants makes the need for parallel processing even more apparent. The proposed Ant Colony Community (ACC) uses a coarse grained approach to parallelization. Two implementations using RMI and Sockets respectively are compared. Results of an experiment prove the ACC is capable of a substantial reduction of processing time.