基于改进麻雀搜索算法的冷链物流路径优化

Optimization of Cold Chain Logistics Path Based on Improved Sparrow Search Algorithm

针对城市间冷链物流对成本与时效的高要求,提出了一种改进的离散麻雀搜索算法。通过对麻雀维度序列的映射,实现了算法的离散化;引入基于维度的邻域模型以加强麻雀种群内的信息交流,降低陷入局部最优解的可能;引入动态因子以改进发现者位置更新公式,平衡算法的开发与勘探。采用23个标准测试函数进行测试,实验所得平均值与方差表明,改进算法的搜索性能与稳定性得到了极大的改善。采用6个标准VRPTW数据集测试改进算法求解复杂路径优化问题的能力,对比实验表明,改进算法能够以更快的速度求得更优的可行解,验证了改进算法的有效性与稳定性。最后使用小规模数据集可视化展示了改进算法在路径规划问题的提升。

Aiming at the high requirements of inter-city cold chain logistics in terms of cost and time efficiency,an improved discrete sparrow search algorithm is proposed.The discrete algorithm is realized by mapping the sparrow dimensional sequences;introducing a dimension-based neighborhood model to enhance the information exchange within the sparrow population and reduce the possibility of falling into local optimal solutions;introducing dynamic factors to improve the discoverer position update formula and balance the development and exploration of the algorithm.Twenty-three standard test functions were used for testing,and the mean and variance obtained from the experiments showed that the search performance and stability of the improved algorithm were greatly improved.Six standard VRPTW datasets were used to test the ability of the improved algorithm to solve complex path optimization problems.The comparison experiments show that the improved algorithm can find better feasible solutions at a faster rate,which verifies the effectiveness and stability of the improved algorithm.Finally,the enhancement of the improved algorithm for the path planning problem is demonstrated visually using a small-scale dataset.