Volume 37, Issue 3 (IJIEPR- 2026)                   IJIEPR 2026, 37(3): 214-239 | Back to browse issues page

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Karimi B, mohammadpour omran M, Sahebi H. Just-in-Time Material Delivery Optimization in Multi-Site Construction through BIM–IoT-Enabled Digital Twin-Based Fourth-Party Logistics. IJIEPR 2026; 37 (3) :214-239
URL: http://ijiepr.iust.ac.ir/article-1-2743-en.html
Just-in-Time Material Delivery Optimization in Multi-Site Construction through BIM–IoT-Enabled Digital Twin-Based Fourth-Party Logistics
Behnam Karimi1 , M. Mohammadpour omran2 , Hadi Sahebi1
1- Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
2- Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran , omran@iust.ac.ir
Abstract:   (606 Views)
Construction material delivery across multiple sites faces uncertain demand, changing site readiness, limited logistics capacity, restricted storage, and transport-related emissions. This study develops a BIM–IoT-driven digital twin for fourth-party logistics (4PL) orchestration of just-in-time material delivery under uncertainty. The framework integrates BIM information with operational data on project progress, shipment status, inventory, site readiness, and logistics availability. A scenario-based multi-objective MILP uses rolling-horizon optimization to minimize logistics cost, delivery deviation, site congestion, and carbon emissions. It distinguishes implemented decisions from immediate decisions and scenario-dependent recourse. Transportation uncertainty is addressed by separating dispatch from arrival and incorporating conditional value at risk. For large instances, an Event-Aware Rolling-Horizon NSGA-II uses scenario-linked encoding, Pareto warm starts, event-affected gene masks, adaptive operators, and hierarchical feasibility repair. In the case application, BIM–IoT digital-twin updating with JIT control reduced delivery deviation by 36.1% and site congestion by 32.2%, while the complete policy achieved 90.6% on-time delivery. Across benchmark classes, ERH-NSGA-II increased hypervolume by 8.4–88.2% and reduced IGD+ by 30.9–85.8% relative to conventional NSGA-II. The framework also provides quantitative decision rules for logistics capacity, storage, data quality, consolidation, and carbon restrictions.
Keywords: Construction logistics, Digital twin, BIM–IoT, Fourth-party logistics, Just-in-time delivery, Rolling-horizon optimization, ERH-NSGA-II.
Full-Text [PDF 988 kb]   (206 Downloads)    
Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2026/06/3 | Accepted: 2026/08/16 | Published: 2026/09/8
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