Optimizing Fruit Fly Algorithm to Solve TSP Problem

Traveling salesman problem is a classical combinatorial optimization problem. Based on solving TSP problem, this paper presents an an optimized fruit fly algorithm. Based on the fruit fly algorithm, the fixed step size is reduced to a decreasing step size, which makes the global optimization ability and local optimization ability form a dynamic balance mechanism. The crossover and mutation operations combined with genetic algorithm not only protect the optimal individuals, but also increase the diversity of the population, and restrain the generation of premature problems. Finally, using the basic fruit fly algorithm and the optimized fruit fly algorithm to solve the TSP problem, it is proved that the improved fruit fly algorithm has better performance in solving the TSP problem.