Optimization of Cold Chain Logistics Path Based on Improved Sparrow Search Algorithm
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 di-mension-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 com-parison 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.