Integrated Inventory Model for Multi Item under Price - Sensitive Demand with Controllable Lead Time and Greenhouse Gas Emission Effect on Production andTransportation
価格感応需要下での多品目統合在庫モデル：リードタイム制御可能及び生産・輸送における温室効果ガス排出影響 (AI 翻訳)
Neetu Rawat, Rakesh Pandey
🤖 gxceed AI 要約
日本語
本研究は、単一ベンダーが複数バイヤーに多品目を供給するサプライチェーンにおいて、温室効果ガス（GHG）排出コストを生産・輸送段階で考慮した統合在庫モデルを提案する。需要は正規分布に従い、リードタイム短縮に費用がかかる。価格感応需要を導入し、総期待費用最小化を目指す。数値例と感度分析によりモデルを検証。
English
This paper proposes an integrated inventory model for a supply chain where a single vendor supplies multiple items to multiple buyers. It incorporates greenhouse gas (GHG) emission costs in production and transportation, considers controllable lead times with crash costs, and price-sensitive demand. The objective is to minimize total expected cost. A numerical example and sensitivity analysis are provided.
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
本研究はサプライチェーンにおけるGHG排出コストを明示的にモデル化しており、日本のScope 3排出削減や物流最適化に示唆を与える。ただし、具体的な政策や開示基準（例：SSBJ、有報）との関連は弱く、実務応用には追加の実証が必要。
In the global GX context
This paper contributes to sustainable supply chain management literature by integrating GHG costs into inventory decisions, aligning with global trends such as CDP supply chain program and the push for Scope 3 reporting. However, it remains theoretical and lacks empirical validation or direct policy linkage.
👥 読者別の含意
🔬研究者:Operations researchers interested in sustainability-oriented inventory models can build on this framework by incorporating real-world data or policy constraints.
🏢実務担当者:Supply chain managers can use this model as a starting point to quantify and optimize emission costs alongside traditional inventory costs.
📄 Abstract（原文）
In today’s era of rapid human advancement, environmental concerns have become just as important as economic and industrial growth. This study examines how greenhouse gas (GHG) emissions affect production and transportation in a supply chain model in which a single vendor supplies multiple items to several buyers. The buyers’ demand is normally distributed, and delivery lead times can be shortened by incurring crash costs. Importantly, the model also incorporates transportation and GHG-related costs during both production and delivery stages. Additionally, the model considers price-sensitive demand, recognizing that fluctuations in price can influence buyer behavior and overall demand levels. The main goal is to minimize the overall expected cost while determining key decision variables, such as each buyer’s lead time, the vendor’s order quantities, and shipment frequency. A numerical example is used to illustrate the model, and a sensitivity analysis explores how changes in key parameters affect the optimal supply chain decisions.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.54536/ajise.v5i2.7091first seen 2026-05-16 04:36:41 · last seen 2026-05-21 04:28:34
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