CV


FA
saeed dehnavi

saeed dehnavi

Assistant Professor

College: Faculty of Engineering

Department: Industrial Engineering

CV
FA
saeed dehnavi

Assistant Professor saeed dehnavi

College: Faculty of Engineering - Department: Industrial Engineering

Sustainable energy-efficient optimization of construction supply chains with smart contracts

Authorsسعید دهنوی آرانی,هادی مختاری
JournalSustainable Futures
IF4.9
Paper TypeFull Paper
Published At2026-01-06
Journal GradeScientific - research
Journal TypeElectronic
Journal CountryIran, Islamic Republic Of
Journal IndexISI-Listed ,SCOPUS
KeywordsEnergy efficiency, Sustainable construction, Blockchain, enabled smart contracts, CO₂ Emissions, Reverse logistics, Mixed, integer linear programming

Abstract

The construction industry is a major global consumer of energy and a leading source of greenhouse gas emissions, underscoring the need for transparent, data-driven, and energy-efficient supply chain strategies. This study develops an integrated mixed-integer linear programming (MILP) model for a multi-echelon, multi-product construction supply chain that explicitly incorporates differentiated building energy efficiency levels (A+, A++, A+++) as exogenous determinants of material requirements, production processes, and logistics flows. By embedding blockchain-enabled smart contracts, the model automates supplier governance and ensures compliance with delivery reliability, quality standards, and CO2 performance through predefined incentives and penalties, thereby enhancing transparency and accountability. The framework jointly optimizes facility location, material and product flows, supplier selection, and reverse logistics operations under a CO₂ emission cap, while simultaneously capturing the implications of greenfield and brownfield project conditions. A real-scale numerical case study demonstrates the model’s ability to evaluate the economic–environmental trade-offs arising from increasingly stringent sustainability requirements. The results reveal that although higher energy efficiency levels incur greater initial supply chain costs due to advanced materials and more complex logistics, they lead to substantial reductions in long-term operational energy consumption, rendering the A+++ option the most economically favorable from a lifecycle perspective. Furthermore, the integration of blockchain-enabled smart contracts partially offsets cost escalations by penalizing non-compliant suppliers and rewarding high-performing ones. Overall, the proposed model provides a rigorous and transparent decision-support framework that enables contractors to align supply chain design with energy-efficiency targets, CO2-reduction policies, and circular- economy objectives while preserving operational feasibility and supply reliability.