Robust Design of Financially Constrained Supply Chain Networks under Demand Uncertainty

The design of resilient supply chain networks that can withstand significant environmental volatility is a paramount challenge for modern enterprises. Strategic network design decisions are complicated by the confluence of operational complexities, pervasive uncertainty, and stringent financial limitations. This paper addresses this challenge by developing a novel robust optimization (RO) model for the design of a multi-echelon supply chain network. The model uniquely integrates critical financial constraints a fixed investment budget for capital expenditures and a dynamic working capital constraint tied to inventory levels into a framework that explicitly manages demand uncertainty. We employ a budgeted uncertainty set to model demand, which allows decision-makers to control the level of conservatism and avoid overly pessimistic solutions. The deterministic mixed-integer linear programming (MILP) model is first formulated and then transformed into its robust counterpart. A computational study is conducted on a series of problem instances to analyze the behavior of the model. The results demonstrate that financial constraints fundamentally alter the structure of an optimally robust network, often shifting hedging strategies away from inventory holding towards capacity buffering or network diversification. The analysis reveals a critical trade-off between total cost, financial feasibility, and the level of robustness. We conclude that ignoring financial constraints during the robust design phase can lead to strategies that are operationally sound but financially infeasible, highlighting the necessity of an integrated approach for strategic supply chain planning.

کلیدواژه ها:

Robust optimization ، Supply chain network design ، Financial constraints ، Demand uncertainty