基于改进沙猫群优化算法的绿色多式联运路径优化OACSTPCD

To solve the problem that there are various factors that affect multi-modal transport logistics and the difficulty in achieving balance between various costs,there are six elements carefully considered:transportation cost,transfer cost,risk cost,fuel consumption cost,carbon emission cost and service timeliness cost.In addition,the energy consumption and emissions of new energy lorries are also considered.Then,a green vehicle logistics multimodal transport model is constructed to better reflect the structure of costs incurred by vehicle multimodal transport logistics.In order to better develop a reasonable distribution plan,a mixed sand cat swarm optimization(MSCSO)algorithm is proposed.Through the sand cat swarm optimization algorithm,random distribution and K-means clustering algo-rithm,the initial sand cat position is optimized.Furthermore,particle collaboration mechanism and random walk strategy are introduced.Through a comparison drawn with other algorithms tested against the benchmark function,it is demonstrated that the proposed algorithm performs better in the accuracy and pace of convergence.Finally,the proposed algorithm is applied to solve the practical problems with multimodal vehicle logistics transportation.The experimental results show that the mixed sand cat swarm optimization algorithm is advan-tageous in multimodal transport path planning.