A Parameter Model of Genetic Algorithm Regulating Ant Colony Algorithm

It is difficult to determine optimal combination parameter which can make the solving performance of ant colony algorithm work better, owing to the bulkiness of parameter space and relevance among parameters. Until now, it has not owned perfect theoretical basis and been obtained mostly by repeated tests. Based on these problems, the paper finds a better combination parameter by balancing exploration and exploitation abilities of ant colony algorithm, building algorithm performance to evaluate the objective function and applying genetic algorithm to solve ant colony parameters. The experimental simulation of classical TSP problem can verify the scheme feasibility. Simulation results indicate that the model has a positive effect on determining ant colony algorithm parameters and offers a feasible scheme for selecting ant colony algorithm combination parameter.