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Title: Multi-modal transportation planning for multi-commodity rebalancing under uncertainty in humanitarian logistics
Authors: Gao, X
Jin, X
Zheng, P 
Cui, C
Issue Date: Jan-2021
Source: Advanced engineering informatics, Jan. 2021, v. 47, 101223
Abstract: Multi-commodity rebalancing plays a critical role before and during the attack of large-scale disasters. In practice, some relief centers can be out of reach from the ground for vehicles due to the road disruption. Accordingly, alternative transportation systems are essential to maximize fairness and minimize the total transportation time, simultaneously. However, little study has reported on this issue for humanitarian logistics. To address it, a bi-objective stochastic optimization model is proposed to rebalance and transport commodities with the multi-modal transportation system. This work first linearizes the model and then applies an adaptive augmented -constraint method to obtain a number of Pareto-optimal solutions. Furthermore, a case study of an emergency event is carried out, of which the computational results indicate its decision making effectiveness. Lastly, sensitivity analysis on critical parameters is conducted and the trade-off between the objectives is also analyzed to provide valuable managerial insights.
Keywords: Multi-modal transportation
Stochastic programming
Commodity rebalancing
Transportation planning
Humanitarian logistics
Publisher: Elsevier
Journal: Advanced engineering informatics 
EISSN: 1474-0346
DOI: 10.1016/j.aei.2020.101223
Rights: © 2020 Elsevier Ltd. All rights reserved.
© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
The following publication Gao, X., Jin, X., Zheng, P., & Cui, C. (2021). Multi-modal transportation planning for multi-commodity rebalancing under uncertainty in humanitarian logistics. Advanced Engineering Informatics, 47, 101223 is available at
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