A dynamic multi-period, mixed-integer linear programming model for cost minimization of a three-echelon, multi-site and multi-product construction supply chain

Quantifying the benefits of construction supply chain management through prescriptive models is a challenging and fast-growing research area that still lacks standardized optimization models with full integrative potential. In response to the needs and the peculiarities of the construction industry, this paper proposes an innovative model that merges temporal and project-based supply chains into a sustainable network with repetitive flows, large scope contracts, strategic alliances and economies of scale. It is a dynamic mixed-integer linear programming model for cost minimization of a three-echelon supply chain serving multiple sites with multiple products over a time horizon. Its novelty lies in yielding optimal decisions on network design, product quantities to be purchased and transported, shipments and inventory levels in all echelons under any logistics system in a multi-period, multi-product and multi-project environment with discount schemes and strategic preferences. The model is general enough to be implemented by any general contractor acting as a system integrator but also allows customization with logical constraints. All these features constitute an innovative, versatile and flexible managerial decision making tool. Model implementation is based on a spreadsheet optimization software and is followed by post-solution analysis, sensitivity analysis and multiple parameterized optimizations.