Solving Traveling Salesman Problem Using Combination Intelligent Techniques and Genetic Algorithm

Various methods have been proposed to solve the traveling salesman problem such as a solution based on genetic algorithm. But in general, these algorithms and especially genetic algorithm are often faced with early convergence in solving combinatorial problem, in this paper we review and introduce new methods and survey to solve the problem. Our idea based on hybrid genetic algorithm for solving the traveling salesman problem. The implementation of our algorithm is that different methods at each step of the algorithm, including initial population by the nearest neighbor, greedy algorithm and combination of them with the genetic algorithm and also different methods for mutation operator has been surveyed. Combining untwist algorithm with genetic algorithm to improve the population and is expected to strengthen the global optimal solution. When the diversity of the population is reduced, artificial chromosomes with high diversity level are introduce to increase the diversity level in the system. Implementation has been shown the improvement result of hybrid algorithm than the pure genetic algorithm.