基于DE算法的改进ACO算法求解旅行商问题

An improved ACO algorithm based on DE for solving traveling salesman problem

以旅行商问题(TSP)为研究对象,提出一种基于差分(DE)算法的改进蚁群算法(ACO&DE)。ACO算法具有快速构造机制,DE算法可以扩展ACO算法的搜索范围,避免蚁群算法陷入局部最优。为了使DE算法适合求解离散TSP问题,对变异算子和交叉算子的策略进行重新设计。同时,在ACO算法中嵌入DE算法来改进解的质量。仿真结果验证了ACO&DE算法在求解TSP问题时的有效性,可以扩展应用到TSP的变型和其他物流运输领域。

The paper proposes an improved ant colony algorithm(ACO&DE)based on the difference algorithm(DE)for solving traveling salesman problem(TSP).The ACO algorithm has a fast construction mechanism,and the DE algorithm can expand the search range of ACO to avoid ant colony algorithm falling into local optima.In order to make DE suitable for solving discrete TSP problems,the strategies of mutation operators and crossover operators have been redesigned.Meanwhile,in the ant colony optimization algorithm(ACO),a DE is embedded to improve the quality of the solution.The simulation results validate the effectiveness of the proposed ACO&DE algorithm in solving TSP problems,which can be extended application to variants of TSP and other logistics and transportation fields.