模拟退火蚁群算法在VRP问题上的应用

Combination Application of Simulated Annealing and Ant Colony Algorithm in VRP Optimization Problem

车辆路径问题是物流系统优化的核心问题,在满足相关需求的情况下需要达到路径最短、成本最低等目的。文章提出一种模拟退火算法和蚁群算法的组合,通过改进蚁群算法相关参数、采用邻域算法对解进行二次搜索,从而改变解的质量并进行优选,以实现在满足相关约束条件下达到路径最短的优化。将该组合算法与基本蚁群算法、改进型的蚁群算法及VRP官网算例进行比较,实验结果表明,该组合算法在时间上和准确度上都有较大的提升,具有较好的应用价值。

Vehicle routing problem is the core problem of logistics system optimization,and the shortest path and the lowest cost are achieved when the relevant requirements are satistied. The VRP optimization problem and its solving method are analyzed. The principle and characteristics of simulated annealing and ant colony algorithm are studied. The idea and method of combination of simulated annealing algorithm and ant colony algorithm are proposed. The parameters of ant colony algorithm are improved,and the neighborhood algorithm is used to search the solution two times. The quality of the solution is optimized. It achieves the shortest path under the condition of relevant constraints. The results of this algorithm are compared with those of basic ant colony algorithm,modified ant colony algorithm and VRP website. Experimental results show that the proposed combination algorithm has a great improvement in time and accuracy,and has good application value.