The construction industry is shifting towards integration, digitization, and automation, necessitating an adaptive logistics system for enhanced performance. Despite this shift, poor supplier performance and lack of collaboration among stakeholders often cause delays and cost overruns. This research addresses these issues by proposing an optimization model for the planning phase of construction projects. The generalized mixed-integer linear programming (MILP) model is developed that optimizes supplier and process selection of construction projects, demonstrated through a numerical study. Results indicate that optimizing these decisions in the planning phase can significantly improve supply chain performance, enabling better cost and time management for construction projects traditional or modular.
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