Multi-period regional low-carbon logistics network planning with uncertain demand

Jiehui Jiang and Dian Sheng

Energy, 2025, vol. 331, issue C

Abstract: This study proposes a multi-period regional low-carbon logistics network planning problem for a logistic authority by assuming uncertain freight demand that can be transported by either road or road-railway intermodal transport modes. The proposed problem aims to minimize the total carbon emissions generated from freight transport activities and total network cost by determining the logistic park capacities and railway freight transport service subsidies subject to a limited budget allocated for each planning period. A bi-objective robust multi-period programming model incorporating a series of period-based bi-level programming problems is formulated for the proposed multi-period regional low-carbon logistics network planning problem. A tailored column-and-constraint generation method is developed to effectively solve the normalized single-objective robust optimization model. Numerical experiments verify that the computational efficiency of the proposed method is superior to that of the enumeration method. Meanwhile, case studies show that the implementation of subsidy strategies reduces carbon emissions by approximately 0.40 %.

Keywords: Logistics; Uncertain freight demand; Robust multi-period optimization; Bi-level programming; Column-and-constraint generation (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:331:y:2025:i:c:s0360544225027100

DOI: 10.1016/j.energy.2025.137068

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