A novel dynamic resource allocation model for demand-responsive city logistics distribution operations

This paper presents a dynamic customer group-based logistics resource allocation methodology for the use of demand-responsive city logistics distribution operations. The proposed methodology is developed based on the following five developmental procedures, including: (1) specification of demand attributes, (2) customer grouping, (3) customer group ranking, (4) container assignment, and (5) vehicle assignment. The numerical results show that the model permits managing both the time-varying customer order data and logistics resources dynamically with the goal of optimal logistics resource allocation. Particularly, both the aggregate operational costs and average lead time are reduced by 27.4% and 8.7%, respectively, in a case study.