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Traveling Salesman Problem (TSP) is one of the most common studied problemsin combinatorial optimization. Given the list of cities and distances betweenthem, the problem is to find the shortest tour possible which visits all thecities in list exactly once and ends in the city where it starts. Despite theTraveling Salesman Problem is NP-Hard, a lot of methods and solutions areproposed to the problem. One of them is Genetic Algorithm (GA). GA is a simplebut an efficient heuristic method that can be used to solve Traveling SalesmanProblem. In this paper, we will show a parallel genetic algorithmimplementation on MapReduce framework in order to solve Traveling SalesmanProblem. MapReduce is a framework used to support distributed computation onclusters of computers. We used free licensed Hadoop implementation as MapReduceframework.

Parallel Genetic Algorithm to Solve Traveling Salesman Problem on MapReduce Framework using Hadoop Cluster