Regional multimodal logistics network design considering demand uncertainty and CO_2 emission reduction target: A system- optimization approach

摘要

This paper investigates an interesting regional multimodal logistics network design problem with CO2 emission reduction target and uncertain demands in the context of urban cluster development. From the perspective of system optimization, a regional logistics network involves a centralized logistics authority and a centralized carrier, where the logistics authority concerns the regional logistics network configuration in terms of the number, location and scale of logistics parks and the subsidies of rail transportation links, and the carrier's decisions include the choice of transportation route for each logistics demand. Given a determined logistics demand pattern, this multi-stakeholder decision making problem is first formulated as a bi-level programming model followed by its equivalent mathematical programming with equilibrium constraints (MPEC) to depict the leader-follower behaviors. To capture the risk aversion level of the logistics authority in uncertain demand environment, an improved adjustable robust optimization method is proposed, including an individual control parameter and providing an exact expression of the maximum satisfaction probability. Computational results and related impact analysis demonstrate that the proposed models and solution methods are effective, which can provide the beneficial theory basis and practice guide for the green and sustainable development of regional logistics. (c) 2019 Elsevier Ltd. All rights reserved.