混合蚁群算法求解无人靶车路径问题研究

Research on Solving the Routing Problem of Unmanned Target Vehicles by the Hybrid Ant Colony Algorithm

针对无人靶车路径过程中效率低成本高的问题,构建了无人靶车路径问题(Routing Problem of Un⁃manned Target Vehicle,RPUTV)的混合整数优化模型,该模型以无人靶车行驶路径距离最小化为优化目标。首先,为了提高算法的求解效率和求解质量,在算法的初始阶段引入贪心算法来构建初始解,同时在蚁群算法中引入了邻域搜索算法组成了混合蚁群算法(Hybrid Ant Colony Algorithm,HACA)来提高算法的局部搜索能力。其次,采用标准数据集来验证算法,同其他求解算法进行对比显示,HACA算法求解RPUTV具有更高效性。

In order to solve the problem of low efficiency and high cost in the process of unmanned target vehicle routing,a mixed integer optimization model for the routing problem of unmanned target vehicles(RPUTV)is con⁃structed,which takes the minimization of the driving route distance of unmanned target vehicles as the optimization goal.Firstly,in order to improve the solving efficiency and quality of the algorithm,in the initial stage of the algo⁃rithm,the greedy algorithm is introduced to build an initial solution,and the neighborhood search algorithm is in⁃troduced into the ant colony algorithm to form a hybrid ant colony algorithm(HACA)to improve the local search ability of the algorithm.Then,the standard data set is used to verify the algorithm,and compared with other solving algorithms,the HACA is more efficient in solving the RPUTV.