Strategic Planning for Sustainable Last-Mile Logistics: Balancing Airspace Constraints and Carbon Price Uncertainty in Truck-Drone Delivery
持続可能なラストマイル物流のための戦略的計画：トラック・ドローン配送における空域制約と炭素価格不確実性のバランス (AI 翻訳)
Chengyou Cui, J J Li
🤖 gxceed AI 要約
日本語
本研究は、厳格な空域規制と炭素価格不確実性を考慮したトラック・ドローン協調配送モデル（VRPDBS）を提案。中国延辺朝鮮族自治州の実データを用いたケーススタディにより、空域制約が配送遅延とコスト増加をもたらす一方、移動基地局戦略で緩和可能であることを示した。また、高炭素価格シナリオではドローン主体の配送が経済的・環境的に優れることを明らかにした。
English
This paper proposes a Vehicle Routing Problem with Drones and Mobile Base Stations (VRPDBS) model incorporating airspace constraints and carbon price uncertainty. Using real data from Yanbian, China, it finds that strict airspace compliance causes 4-5 hour delays and up to 15% cost premium, mitigated by mobile base stations. Under high carbon prices, drone-intensive configurations show superior economic and environmental performance.
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
中国の国境地帯を事例に、空域制約と炭素価格不確実性を考慮したドローン配送モデルを提案。日本の過疎地域物流やカーボンプライシング導入の参考になる。
In the global GX context
This study addresses sustainable last-mile logistics under airspace constraints and carbon pricing, offering a decision-support framework for regions with complex regulations. It highlights how carbon price uncertainty can shift optimal logistics configurations, relevant for global climate policy adaptation.
👥 読者別の含意
🔬研究者:Provides a new VRPDBS model integrating airspace flyability and carbon price sensitivity, valuable for sustainable logistics optimization research.
🏢実務担当者:Offers strategic insights for logistics firms to evaluate truck-drone mix under carbon pricing and airspace constraints, supporting resilient green logistics planning.
🏛政策担当者:Demonstrates how carbon pricing and airspace regulations interact with logistics efficiency, informing integrated climate and transport policy design.
📄 Abstract（原文）
The accelerated growth of e-commerce has intensified the dual challenges of weak infrastructure and carbon emission pressures in last-mile delivery for rural and mountainous regions. As the World Bank calls for integrating carbon market development into national strategies, Truck-Drone Collaborative Delivery (TDCD) has emerged as a critical sustainable solution. However, existing research often overlooks the strict airspace regulations in sensitive border areas. Therefore, this paper proposes a Vehicle Routing Problem with Drones and Mobile Base Stations (VRPDBS) model that explicitly incorporates airspace constraints and mobile hub deployment. We introduce a quantified “Regional Flyability Factor” (fk) to measure the impact of airspace restrictions on routing decisions and solve the problem using a hybrid metaheuristic algorithm. A case study based on real-world data from the Yanbian Korean Autonomous Prefecture reveals that strict airspace compliance imposes an absolute delivery delay of 4–5 h and an operational cost premium of up to 15%, an impact that can be effectively mitigated through a mobile base station mediation strategy. More importantly, multi-scenario sensitivity analysis under carbon price uncertainty indicates that although truck-dominant modes are cost-effective at current low carbon prices, drone-intensive configurations demonstrate superior economic robustness and environmental performance under high carbon price scenarios. This study not only provides a technical framework for green logistics planning in complex airspace but also offers strategic decision support for logistics enterprises to navigate long-term climate policy risks.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18083978first seen 2026-05-05 19:13:59
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