Cell-based membrane evolutionary algorithm for solving the Travelling Salesman Problem
The paper explores a method to solve the Travelling Salesman Problem by combining a cell-based membrane evolutionary algorithm.Firstly,the algorithm constructs a cell-based membrane structure model and takes advantage of the great parallelism of membrane systems to initialize the population in the elementary membrane by Hybrid Particle Swarm Optimization.Then,the global optimal solution of the path is iteratively optimized by splitting,fusion,dissolution,and repair operators of the membrane evolutionary algorithm.Finally,based on the fitness of each elementary membrane,the membrane with the highest fitness value is selected as the solution of the TSP.In the experiments,the algorithm is applied to several TSP instances and compared with traditional Particle Swarm Optimization and Genetic Algorithm,etc.The experimental re-sults show that the proposed algorithm exhibits better convergence and search capabilities in solving the TSP,significantly improving the solution results.
万方数据
维普
