A green vehicle routing methodology for assessing optimal fleet mix and cost/emissions tradeoffs given environmental policy incentives
環境政策インセンティブに基づく最適なフリートミックスとコスト・排出量トレードオフ評価のためのグリーン車両ルーティング手法 (AI 翻訳)
Griffin M. Wilson, Richard T. Stone
🤖 gxceed AI 要約
日本語
本論文は、炭素税、排出権取引（ETS）、電気自動車補助金といった政策手段が企業のフリートミックスとルーティング選択に与える影響を分析するための二目的グリーン車両ルーティング問題を提案する。パレート最適解の変化を分析することで、最も費用対効果の高い排出削減経路を特定する手法を提供する。
English
This paper develops a bi-objective green vehicle routing problem to assess optimal fleet mix and routing under carbon taxes, emissions trading systems, and electric vehicle subsidies. By analyzing shifts in the Pareto frontier, it identifies cost-effective routes for reducing greenhouse gas emissions, providing firms with a decision-making tool under varying policy scenarios.
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
日本でも炭素価格制度やEV補助金が導入されており、本手法は企業のフリート戦略策定に応用可能。特に、物流分野の脱炭素化に向けた政策評価に示唆を与える。
In the global GX context
This methodology offers a practical framework for firms globally to evaluate tradeoffs between cost and emissions under different carbon pricing and subsidy regimes. It is relevant for policymakers designing incentives for fleet electrification and for logistics companies navigating the transition to low-carbon transportation.
👥 読者別の含意
🔬研究者:Offers a novel optimization model for studying policy impacts on fleet composition and routing.
🏢実務担当者:Can be used by logistics firms to assess cost and emissions benefits under different policy scenarios.
🏛政策担当者:Provides insights into how carbon pricing and subsidies influence fleet electrification decisions.
📄 Abstract（原文）
Transportation accounts for nearly one quarter of global greenhouse gas (GHG) emissions. A significant proportion of transportation emissions can be attributed to supply chain transport, which also represents the fastest-growing sector of emissions. As a way of addressing this challenge in the effort to combat global climate change, many local and national governments have leveraged public policy in the form of carbon taxes, emissions trading systems (ETSs), and subsidies for heavy goods electric vehicles (HGEVs). Firms affected by these policies are thus faced with higher costs for more emissions-intensive supply networks and a lower barrier to entry towards adopting HGEVs. However, the exact policy conditions under which firms would be most motivated to change their behaviors remains unclear. In this paper, we develop a novel methodology to address this obstacle in the form of a bi-objective green vehicle routing problem. The first objective is the minimization of the total cost of transportation over a set of vertices comprised of a depot, customers, and charging stations; the second objective is the minimization of total GHGs emitted during transportation. The proposed approach considers the three policy instruments and their effects on both fleet mix decisions (i.e., the conditions under which a firm is most motivated to adopt HGEVs) and cost- and GHG-minimizing routing options. Via an analysis of the change of the Pareto frontier given increasingly stringent carbon pricing and/or increasingly generous HGEV subsidies, firms may consider routing options that yield the most significant GHG emissions reduction at the lowest cost. To this end, we provide a survey of current and forecasted global trends related to carbon tax rates, ETS carbon allowance prices, and HGEV subsidy amounts.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.1371/journal.pcsy.0000092first seen 2026-05-14 21:17:52
🔔 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。