An Investigation of Multimodal Transport for Last Mile Delivery in Rural Areas

Abstract

High distribution costs constitute one of the major obstacles to the sustainable development of rural logistics. In order to effectively reduce the distribution costs of last mile delivery in rural areas, based on three typical transport modes (local logistics providers, public transport, and crowdsourcing logistics), this study first proposes a multimodal transport design for last mile delivery in rural areas. Then, a cost–benefit model for multimodal transport is proposed which uses genetic algorithms (GA) to solve the logistical problems faced. Finally, Shapley value is used to fairly allocate profits and represent the marginal contribution of each mode in multimodal transport. The numerical results show that multimodal transport can effectively reduce the distribution costs of last mile delivery in rural areas. When the order demand of each node tends to be stable, the marginal contribution of crowdsourcing logistics is often greater than that of the other two distribution modes. The marginal contribution of public transport is highest only when the number of orders per node is very small.