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The combination of genetic algorithm and local search is a promising approach that attempts to benefit the advantageous of both approaches in solving the traveling salesman problem. In this paper we present a 2opt-DPX genetic local search algorithm for solving symmetric TSP instances. The main idea of this approach is to use a local search heuristic to create population of local optimum solutions and then applying genetic algorithm to find global optimum in the population of local optima. We describe its performance on some standard symmetric TSP instances and finally put forward some suggestions to improve its capability and efficiency.