A MILP-Based Two-Echelon Logistics Network Design Model Under Uncertainty: Application to a Perishable Banana Supply Chain

Background: Perishable agri-food supply chains require logistics networks that remain economically viable despite fluctuations in demand, transportation costs, and market prices. This study develops and evaluates a two-echelon logistics network for the banana supply chain in Magdalena, Colombia. Methods: A mixed-integer linear programming model was formulated to maximise daily profit by jointly determining collection-centre activation and product flows among 14 producers, five candidate collection centres, and two commercial buyers. The deterministic solution was complemented by sensitivity analysis and 1000 Monte Carlo optimisation scenarios incorporating variability in demand, transportation costs, and selling prices. Results: Under nominal conditions, all five collection centres were activated, the full demand of 42,000 kg/day was served, and the optimal profit was USD 3093/day. Centres C1–C4 operated at full capacity, whereas C5 reached 42.9% utilization. Under uncertainty, the mean profit decreased to USD 1955.70/day, the mean unmet demand was 954.03 kg/day, and shortages occurred in 72.3% of scenarios. C1–C4 remained the network core, while C5 acted as a flexible contingency facility. Conclusions: The proposed framework reveals an efficiency–resilience trade-off overlooked by deterministic optimisation. Demand growth and capacity reductions are the principal operational risks, supporting investment in collection capacity and proactive demand management.