Abstract
The Travelling Salesman Problem (TSP) is one of the most widely and deeply studied problems in optimization. It belongs to the category of NP Complete problems in which no polynomial time solution is possible unless P=NP. Various researches are done on finding efficient heuristics to get provably optimal and near to optimal results to TSP. Having the push towards grid and cloud computing, it will become more necessary to adopt existing algorithms to distributed computing frameworks like MapReduce. The aim is to parallelize the ant colony optimization algorithm for solving TSP over the Apache Hadoop MapReduce framework. The paper also compares the results of the parallel implementation with the performance of the serial version of the ACO algorithm.
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