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Optimization of the Travelling Salesman Problem Using a New Hybrid Genetic Algorithm


Zakir Hussain Ahmed, Furat Fahad Altukhaim, Abdul Khader Jilani Saudagar, and Shakir Khan


Vol. 24  No. 3  pp. 12-22


The travelling salesman problem is very famous and very difficult combinatorial optimization problem that has several applications in operations research, computer science and industrial engineering. As the problem is difficult, finding its optimal solution is computationally very difficult. Thus, several researchers have developed heuristic/metaheuristic algorithms for finding heuristic solutions to the problem instances. In this present study, a new hybrid genetic algorithm (HGA) is suggested to find heuristic solution to the problem. In our HGA we used comprehensive sequential constructive crossover, adaptive mutation, 2-opt search and a new local search algorithm along with a replacement method, then executed our HGA on some standard TSPLIB problem instances, and finally, we compared our HGA with simple genetic algorithm and an existing state-of-the-art method. The experimental studies show the effectiveness of our proposed HGA for the problem.


Travelling salesman problem; Hybrid genetic algorithm; Comprehensive sequential constructive crossover; Adaptive mutation; Local search; Replacement method.