Based on improved genetic algorithm for TSP
Liu Hua-bin · Jisuanji gongcheng yu sheji · 2007
TSP (traveling salesman problem) is also referred to as traveling salesman problem. TSP is NP-complete problem, and genetic algorithms (GA) which resolves the problem of combination arrangement occupies a very important position. A modified genetic algorithm is suggested. By employing exchange heuristic crossover operator and variable crossover probability to achieve local search algorithm, which accelerates convergence, by employing the mutation operator and variable mutation probability to maintain the diversity of groups, which prevents genetic algorithm to convergence in advance. Through Java simulation results show that the improved algorithm is superior to the traditional genetic algorithm and has good validity and feasibility.