カーボンニュートラル達成に向けた効果的な排出量取引の活用
Exploitation of Effective Emission Trading to Aim Carbon Neutrality (原題)
Yo-Der Huang, Unaffiliated, Chun-Che Huang, Tzu-Liang (Bill) Tseng
🤖 gxceed AI 要約
日本語
カーボンニュートラル達成に向け、買い手と売り手を多目的にマッチングする排出量取引（ET）問題を扱う。進化的多目的最適化（EMO）に基づくEMOBETを提案し、買い手コスト最小化・売り手利益最大化・SD観点の評判最大化・マッチ数最大化を同時に探索する。ESGデータを用いた追跡可能な評判スコアにより、参加者と規制者が削減目標達成を信頼できる形で確認できる点が貢献。
English
This study addresses emission trading (ET) as a multi-objective matching problem between polluters and green entities. It proposes EMOBET, an evolutionary multi-objective optimization approach that simultaneously minimizes buyer cost, maximizes seller profit, maximizes SD-based buyer reputation, and maximizes matches. Traceable reputation scores built on ESG data aim to let participants and regulators credibly verify carbon reduction goals.
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GXリーグやカーボン・クレジット市場、SSBJ開示と連動する形で、ESG評判を組み込んだ取引マッチングの設計は、国内排出量取引制度の制度設計や企業のカーボン調達戦略に示唆を与える。
In the global GX context
Globally, this contributes to the design of carbon markets and disclosure infrastructure by integrating ESG-based reputation into ET matching, relevant to Article 6, voluntary carbon markets, and ISSB-linked assurance of carbon claims.
👥 読者別の含意
🔬研究者:多目的最適化とESG評判を統合した排出量取引モデルの新規性と限界を検証する材料になる。
🏢実務担当者:カーボンクレジット調達やESG評価を踏まえた取引相手選定の意思決定に応用できる可能性がある。
🏛政策担当者:排出量取引制度設計において、評判スコアや多目的マッチングを組み込む際の参考になる。
📄 Abstract（原文）
“A livable climate, carbon neutrality commitments must be backed by credible action” which is delivered by the UN as an emergency goal. To pursuit the carbon neutrality, the emission trading (ET) problem, which concerns a matching solution between a polluter and a green entity with multiple objectives is exploited. Particularly, the solution approach should provide a traceable reputation score to market users with, ESG (Environmental, Social and Governance) data. In such way, participants and regulators can trustfully ensure that carbon reduction goals can be met. The ET problem does not only concern a matching solution between buyers and sellers, but also with multiple objectives, such as buyer’s low cost, seller’s high profit, and so on. In this study, an effective, open, and fair ET to match the buyers and sellers is proposed. To solve this ET problem, the Evolutionary Multi-objective Optimization (EMO) Based ET (EMOBET) approach is proposed to uncover candidate solutions based on the simultaneous consideration of multiple, potentially conflicting objectives. The deliverables of this study are composed of the matching solution of buyers and sellers and the results of multiple objectives, including minimizing cost of buyers, maximizing profit of sellers, maximizing the total buyers’ reputation from the perspectives of SD, maximizing the number of matching. This research results are expected to contribute: (1) Reference for Government carbon neutrality strategy, (2) Networking for Business carbon trading, and (3) Enhancement for Organization sustainability.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.21872/annual2025_6093first seen 2026-10-02 04:47:34
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