A Reverse-Logistics Goal-Programming Framework for Post-Conflict Rubble Management in Aleppo with MCDM-Based Evaluation
アレッポの紛争後のがれき管理のための逆物流ゴールプログラミングフレームワーク：MCDMに基づく評価 (AI 翻訳)
J. Hallak, A. H. Abdul Hafez
🤖 gxceed AI 要約
日本語
アレッポ市の紛争後のがれき管理を対象に、逆物流ネットワークの多目的最適化モデルを提案。コスト、CO2排出、社会的受容性、運用リスクの4目的を重み付きゴールプログラミングで定式化し、4つの手法を比較した。30%のリサイクル補助金が最も効果的であり、単なるコストや排出量だけでなく社会的要素も重要であることを示した。
English
This study develops a multi-objective reverse-logistics model for post-conflict rubble management in Aleppo, considering cost, carbon emissions, social acceptance, and operational risk. Four goal-programming formulations are compared, with weighted goal programming ranking highest. Policy analysis shows a 30% recycling subsidy most improves outcomes, highlighting the need to integrate social and operational factors alongside cost and emissions.
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
日本では地震・台風などの大規模災害後のがれき処理が課題となっており、本モデルのようにコスト・CO2・社会的受容性を同時に考慮する枠組みは、日本の災害廃棄物計画にも示唆を与える。
In the global GX context
While focused on Aleppo, this paper offers a replicable multi-objective framework for rubble logistics that integrates carbon emissions and social acceptance—relevant for climate-resilient reconstruction in conflict-affected or disaster-prone regions globally.
👥 読者別の含意
🔬研究者:Provides a multi-objective optimization framework for rubble logistics with social and CO2 dimensions, and compares goal-programming variants.
🏢実務担当者:Can be adapted for disaster waste management planning in cities prone to conflict or natural disasters, incorporating cost, carbon, and community acceptance.
🏛政策担当者:Highlights the importance of subsidies and multi-criteria evaluation in post-disaster reconstruction policy.
📄 Abstract（原文）
Rubble management in Aleppo is a complex recovery planning problem because debris removal is closely linked to transport access, recycling capacity, reconstruction demand, disposal limits, and local acceptance. This study develops a multi-objective reverse-logistics model for managing post-conflict rubble in the city. The proposed network consists of 21 rubble source nodes, 5 collection and sorting sites, 4 recycling facilities, 5 reconstruction-demand nodes, and 2 disposal sites. The model is formulated as a weighted non-preemptive goal programming problem that considers four objectives: total cost, carbon emissions, dust/social acceptance penalty, and operational implementation risk. Because the last two objectives are strongly context-dependent, they were developed through a Delphi process with 13 experts, and the related subcriteria were weighted using fuzzy FUCOM. Four compromise formulations were tested: weighted goal programming (WGP), augmented max–min fuzzy goal programming (AMM-FGP), weighted additive fuzzy goal programming (WA-FGP), and Max–Min optimization. The resulting solutions were ranked using MARCOS and validated using CRADIS. WGP ranked first, with a MARCOS utility score of 0.697919, followed by Max–Min at 0.654658, AMM-FGP at 0.633123, and WA-FGP at 0.629647. The policy analysis also showed that a 30% recycling subsidy produced the largest improvement, reducing the WGP achievement value from 0.192 to 0.046. These results suggest that, for Aleppo, a rubble-management plan cannot be judged only by cost or emissions. Social nuisance, site operability, and policy support also affect whether a technically efficient network can be implemented in practice.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://www.mdpi.com/2227-7390/14/13/2380/pdf?version=1783082883first seen 2026-07-09 05:51:15
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