Enhancing Supply Chain Coordination Using Mathematical Modeling

Abstract

Effective Coordination across different entities of a supply chain is a critical factor in improving overall efficiency, reducing costs, and increasing responsiveness to market dynamics. This study presents a mathematical model to enhance supply chain coordination by optimizing order and resource allocation among suppliers, manufacturers, and distributors. The proposed model integrates key decision variables, production quantities, transportation capacities, and inventory levels into a mixed-integer Linear Programming (MILP) formulation. By minimizing total system costs and balancing the objectives of all partners, the model promotes cooperative decision-making and reduces the bullwhip effect. The model’s performance was validated using numerical experiments and sensitivity analyses, demonstrating its ability to improve coordination efficiency and stability under varying demand and supply conditions. The data were evaluated using expert opinion and a mathematical equation in GAMS. The results showed that the Coordination of contractor and supplier orders is mainly in the sensitivity analysis group, as reflected in the objective function values. Moreover, the proposed model showed that optimizing order management and unit earnings based on it has functional and developmental capabilities.