An Improved Greedy Genetic Algorithm for Solving Travelling Salesman Problem

Genetic algorithm (GA) is too dependent on the initial population and a lack of local search ability. In this paper, an improved greedy genetic algorithm (IGAA) is proposed to overcome the above-mentioned limitations. This novel type of greedy genetic algorithm is based on the base point, which can generate good initial population, and combine with hybrid algorithms to get the optimal solution. The proposed algorithm is tested with the Traveling Salesman Problem (TSP), and the experimental results demonstrate that the proposed algorithm is a feasible and effective algorithm in solving complex optimization problems.