Multimodal Transport Path Selection of Cold Chain Logistics Based on Improved Particle Swarm Optimization Algorithm

Abstract

Multimodal transport is a process of effectively moving cargoes in a single container by combining land transport (road or rail) and maritime or river transport (vessel or barge) in one transport chain. However, cold chain logistics (CCL), as a special while major kind of cargo delivery, has not been incorporated with this beneficial combination. In order to realize efficient delivery of cold chain foods (CCF), in this study, the characteristics of multimodal and CCL are analyzed and integrated to select the optimal logistics path. In establishing the path-selection model, customer satisfaction is introduced, which is reflected by arrival punctuality and the quality of CCF. An improved particle swarm optimization algorithm (IPSO) is introduced to address the model and is proven to retain a fast convergence rate and achieve outstanding solving accuracy through the experimental study. Sensitivity analysis is also conducted to present the impact of railway speed and cost variation on path selection. Results show that compared with highway transport, railway transport is preferable to the medium and long distance. The influence of railway speed improvement is more striking than cost reduction in motivating decision makers to choose railway transport mode in logistics operations.