Improved Optimal Path Algorithm Based on Ant Colony Algorithm
Ant colony algorithm is based on Ant System(AS)and it is a very important group intelligence algorithm,which is used in many fields,but there are also some shortcomings.The classical ant colony algorithm is analyzed and studied,and an improved P-ACS algorithm is proposed based on ACS algorithm in this paper.Through analysis and experiment,it is found that although the performance of ACS algorithm is higher than AS algorithm,there are still some problems,such as: falling into local optimal solution,search stagnation,and slow initial convergence.The important reason for the above problems is that the pheromone update can not accurately reflect the actual situation of the path.Aiming at this problem,a P-ACS ant colony algorithm is proposed based on particle swarm optimization algorithm(PSO).The algorithm optimizes the pheromone update strategy from three aspects: pheromone concentration range setting,initial pheromone setting and global update strategy improvement.
Ant colony algorithm ACS particle swarm optimization algorithm P-ACS
Zhaohua Long Ruifang Dong
Chongqing University of Posts and Telecommunications,Chongqing 400065,China
国际会议
重庆
英文
144-150
2019-05-30（万方平台首次上网日期，不代表论文的发表时间）