A decision support system for public logistics information service management and optimization

Transportation optimization usually aims at minimizing the empty load ratios (ELRs) of vehicles. Most Chinese vehicles for logistics are owned by individual entrepreneurs. Because China is very large, transport distances are typically long, and thus the ELR is very high. The ELR is the primary reason for high transport costs, considerable pollution, and high energy consumption. Many Chinese local governments try to build public transport information services that decrease the ELR. This work proposes a decision support system (DSS) for public logistics information service management and optimization (PLISMO) for vehicle drivers and owners, logistics customers and related logistics service providers and management institutes. The dynamic and real-time matching model between goods and vehicles, and the enabling technologies are important issues for the DSS for PLISMO. Therefore, intelligent positioning technologies are employed to acquire and manage the vehicle status. A model matching vehicles with goods is developed based on an assessment model of transport capability and service priority criteria. A multi-objective real-time scheduling model is devised to minimize the ELR. Based on the concepts and decision-making models for PLISMO, a DSS is created and the architecture of the system is investigated. The effectiveness of the DSS and decision-making models is demonstrated by a case of finished vehicle logistics (FVL). Analytical results show that the proposed DSS can reduce the ELR and logistics cost. This system helps governments construct DSSs for general PLISMO. (C) 2013 Elsevier B.V. All rights reserved.