In crisis situations, the effective design of humanitarian supply chain is crucial due to the critical nature of relief items, limited resources, and the need for rapid response and high resilience. This study proposes a mixed-integer programming model for designing a humanitarian supply network aimed at maximizing economic efficiency, where strategic decisions regarding facility location, allocation, and flow of essential items are integrated. To address uncertainties in key parameters and operational conditions, a scenario-based robust optimization approach is employed, ensuring the stability and reliability of decisions under varying crisis scenarios. The model is implemented and solved using GAMS, with input data generated from realistic hypothetical crisis scenarios. Sensitivity analysis is also conducted to evaluate the model’s response to changes in critical parameters. Results indicate that the proposed model not only enhances the economic performance of the network but also improves flexibility and reduces the vulnerability of the humanitarian supply chain, providing a practical tool for strategic decision-making in crisis management.