Improve Efficiency of Symmetric Travelling Salesman Problem by Applying Modified Crossover Operator

Genetic algorithm (GA) is a powerful evolutionary searching technique that is used successfully to solve and optimize problems in different research areas. Genetic Algorithm (GA) considered as one of optimized methods which have been used in solving Traveling salesman Problem (TSP). Efficiency of TSP solution depends on efficiency of GA operators; encoding method, population size, number of generations. In specific, crossover plays a significant role in finding possible solution for Symmetric TSP (STSP). In addition, crossover should be determined and enhanced in term of reaching optimal solution. In This paper, we spot the light on using modified crossover method which called Modified sequential constructive crossover and its impact on reaching optimal solution. To justify the relevance of parameters value in solving TSP, a set comparative analysis has been conducted depends on crossover and its probability.