In this paper we study different parallel implementations of the Savings based Ant System algorithm developed for solving the Vehicle Routing Problem. We analyze the effects of low-level parallelization, multiple search strategies and domain decomposition approaches. For the different strategies speedup and efficiency as well as solution quality are reported. Different information exchanges are analyzed within the multiple search strategies.

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Abstract. In this paper we first provide a thorough performance comparison of the three main Ant Colony Optimization (ACO) paradigms for the Vehicle Routing Problem (VRP), namely the Rank based Ant System, the Max-Min Ant System and the Ant Colony System. Based on the results of this comparison we then implement a parallelization strategy to increase computational efficiency and study the effects of increasing the number of processors.

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