Multiobjective optimization of vehicle multimodal transport paths considering carbon emissions: a hybrid genetic-tabu search approach
車両のマルチモーダル輸送経路の多目的最適化における炭素排出量の考慮：ハイブリッド遺伝的タブーサーチアプローチ (AI 翻訳)
Fuyang Zhao
🤖 gxceed AI 要約
日本語
本研究は商用車のマルチモーダル輸送経路最適化において、炭素排出とコストを考慮した多目的最適化モデルを構築し、GA-TSハイブリッドアルゴリズムを提案。長江流域を事例に炭素取引と炭素税政策下での最適経路を比較し、炭素価格上昇が低炭素輸送への移行を促進することを示した。
English
This study develops a multi-objective optimization model for multimodal transport routes considering carbon emissions and costs, using a hybrid genetic-tabu search algorithm. A case study in the Yangtze River Basin compares carbon trading and carbon tax policies, finding that higher carbon prices incentivize low-carbon transport choices.
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
本論文は中国の長江流域を対象としているが、日本の物流部門のGHG削減やカーボンプライシング政策（炭素税・排出量取引）の効果分析に応用可能。日本のGX実践においても、マルチモーダル輸送の最適化はScope3削減に寄与するため示唆に富む。
In the global GX context
This paper offers insights for global supply chain decarbonization by modeling carbon pricing impacts on multimodal transport choices. While the case is Chinese, the methodology is transferable to any region considering carbon trading or carbon tax, including under TCFD/ISSB frameworks.
👥 読者別の含意
🔬研究者:Provides a novel GA-TS algorithm for multimodal transport optimization under carbon pricing scenarios.
🏢実務担当者:Can inform logistics and supply chain managers on cost-effective low-carbon route planning.
🏛政策担当者:Illustrates how carbon trading vs. carbon tax policies affect transport modal shifts.
📄 Abstract（原文）
This study focuses on the optimization of multimodal transportation routes for commercial vehicles, constructing a multi-objective optimization model considering carbon emissions, transportation costs, etc., and designing a genetic taboo search hybrid algorithm (GA-TS) to solve it. Taking the transportation network in the Yangtze River Basin as a case study, compare the optimal path and cost under carbon trading and carbon tax policies. The results indicate that the optimal path under carbon trading policy is "Chongqing→Jingzhou→Wuhan→Huangshi→Anqing→Shanghai", using rail public water intermodal transportation; Under the carbon tax policy, the carbon emissions of railway transportation throughout the entire journey have been reduced, but the proportion of transportation costs is high. Extending the time window can reduce costs, but excessively relaxing or increasing storage costs. The increase in carbon prices or tax rates promotes enterprises to shift towards low-carbon transportation, and research has verified the efficiency of the GA-TS algorithm, providing reference for the industry's green transformation.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1117/12.3096030first seen 2026-05-05 22:54:15
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。