en زنجیره تامین و لجستیک Logistic & Apply Chain پژوهشي Research <div style="text-align: justify;"><span style="font-size:10pt"><span style="font-family:&quot;Times New Roman&quot;,serif"><i><span style="font-size:12.0pt"><span style="color:black">Construction material delivery in multi-site projects is challenged by uncertain demand and site readiness, limited logistics capacity, restricted storage space, and transportation-related emissions. This study develops an uncertainty-aware BIM&ndash;IoT-driven digital-twin framework for fourth-party logistics orchestration of just-in-time and low-carbon material delivery. The framework integrates BIM-based material and activity information with operational observations of project progress, shipment status, inventory, site readiness, and logistics-resource availability. A scenario-based multi-objective mixed-integer linear programming model is formulated within a rolling-horizon structure to minimize expected logistics cost, risk-adjusted delivery deviation, site congestion, and carbon emissions. Implemented decisions, immediate non-anticipative decisions, and future scenario-dependent recourse decisions are distinguished, while transportation uncertainty is represented by separating dispatch and arrival and incorporating conditional value at risk. For large-scale instances, an Event-Aware Rolling-Horizon NSGA-II is developed using scenario-linked encoding, Pareto warm starts, event-affected gene masks, adaptive operators, and hierarchical feasibility repair. Results from an Iranian steel-construction application and multi-size benchmarks show improved delivery, congestion, emission, hypervolume, and IGD+ performance relative to tested baseline policies and algorithms. The framework also yields quantitative decision rules for logistics capacity, site storage, data quality, consolidation, and carbon restrictions.</span></span></i></span></span></div> Construction logistics, Digital twin, BIM–IoT, Fourth-party logistics, Conditional value at risk, Rolling-horizon optimization, Low-carbon delivery. 0 0 http://ijiepr.iust.ac.ir/browse.php?a_code=A-10-209-1&slc_lang=en&sid=1 Behnam Karimi karimi_be@ind.iust.ac.ir 1800319475328460015410 1800319475328460015410 No Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran M. mohammadpour omran omran@iust.ac.ir 1800319475328460015411 1800319475328460015411 Yes Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran Hadi Sahebi hadi_sahebi@iust.ac.ir 1800319475328460015412 1800319475328460015412 No Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran