Considering Service Priority in Multimodal Transport Route Selection Under the Uncertainty of Carbon Trading Prices
炭素取引価格の不確実性下におけるサービス優先度を考慮したマルチモーダル輸送経路選択 (AI 翻訳)
Junhong Hu, Kaiyang Liu, Zhicheng Zhang, Z H Wang, Renjie Luo
🤖 gxceed AI 要約
日本語
本研究は、炭素取引価格の不確実性下で、サービス優先度がマルチモーダル輸送経路選択に与える影響を調査した。炭素価格変動を「炭素Kライン」分布でモデル化し、貨物の時間価値でサービス優先度を定量化。区間ロバスト最適化モデルとカタストロフィ適応遺伝的アルゴリズムを用いて、総コスト最小化を図った。3つの輸送タスクのケーススタディにより、サービス優先度導入で貨物時間価値損失が12.64%削減、炭素価格不確実性は鉄道シェアを10.86%増加させた。
English
This study investigates the impact of service priority on multimodal transport route selection under carbon trading price uncertainty. It models carbon price fluctuations using a 'carbon K-line' distribution and quantifies service priority via cargo time value. An interval robust optimization model solved by a catastrophe-adaptive genetic algorithm minimizes total costs, including carbon emission costs. Case studies of three transport tasks show that incorporating service priority reduces cargo time value loss by 12.64% and decreases comprehensive costs by 2.26%; carbon price uncertainty increases rail transport share by 10.86% and raises comprehensive costs by 3.48%.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では、2026年度からの排出量取引制度本格化に伴い、物流分野での炭素コスト管理が重要となる。本論文のサービス優先度と炭素価格変動を考慮した経路選択モデルは、日本の物流事業者や荷主がカーボンプライシング対応を強化する上で参考になる。また、SSBJ等の開示基準で求められるサプライチェーン排出量削減にも寄与する。
In the global GX context
With carbon pricing expanding globally, this paper offers a practical model for multimodal operators to balance cost, service priority, and emission reduction under carbon price uncertainty. The findings are relevant for firms subject to carbon trading schemes (e.g., EU ETS, China ETS) and for integrating carbon costs into supply chain decisions, aligning with TCFD and ISSB disclosure expectations.
👥 読者別の含意
🔬研究者:Presents a novel optimization model combining service priority, carbon price uncertainty, and multimodal transport, offering a foundation for further studies on low-carbon logistics.
🏢実務担当者:Provides a decision-support tool for transport operators to minimize total costs including carbon costs while maintaining service priority, aiding in route selection under carbon pricing.
🏛政策担当者:Highlights the impact of carbon price uncertainty on mode choice and costs, informing the design of carbon pricing mechanisms to promote low-carbon freight.
📄 Abstract（原文）
To investigate the impact of transfer node service priority on multimodal transport path selection under carbon trading price uncertainty, this study models carbon price fluctuations using a “carbon K-line” distribution and quantifies service priority via cargo time value, optimising node service processes for multi-task handling. An interval robust optimisation model is formulated to minimise total transport costs (including transport, time, cargo time value, and carbon emission costs), subject to constraints such as service priority, transfer capacity limits, and mixed time windows. The model is solved using a catastrophe-adaptive genetic algorithm with Monte Carlo sampling. Case studies of three transport tasks reveal that (1) incorporating service priority alters transport paths, reducing total cargo time value loss by 12.64% and decreasing comprehensive costs by 2.26%; (2) carbon price uncertainty increases rail transport distance share by 10.86% on average and raises carbon emission cost proportions by 0.23%, ultimately increasing comprehensive costs by 3.48%. These findings assist multimodal operators in holistically evaluating cargo types, shipper requirements, and carbon markets. By forecasting carbon prices and implementing service priority, stakeholders can select low-carbon intermodal paths that balance cost efficiency, service priority, and emission reduction, thereby supporting sustainable freight transport decision-making.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18125794first seen 2026-06-10 05:03:33
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