Application of a Genetic Algorithm with Random Crossover and Dynamic Mutation on the Travelling Salesman Problem
Jia Xu, Lang Pei, Zhu Rong-zhao · Procedia Computer Science · 2018
Travelling salesman problem is a combinatorial optimization problem with wide application background and important theoretical value. The traditional method is only suitable for solving small scale travelling salesman problems, thus limiting the application and popularization of such methods. Based on genetic algorithm, the paper proposes an improved strategy combining random crossover and dynamic mutation to increase population diversity and optimize mutation characters. The simulation results show the convergence rate and the optimal solution of the improved algorithm in the paper are obviously superior to the traditional genetic algorithm, the adaptive crossover probability genetic algorithm and the improved selection genetic algorithm, and it provides a new method for the travelling salesman problem.