Data Envelopment Analysis (DEA) for Modeling Efficiency in the Deployment of Military Units for Humanitarian Missions

Data Envelopment Analysis (DEA) is a non-parametric method for evaluating the efficiency of decision-making units with similar functions operating under comparable conditions. In humanitarian missions, particularly during crises, identifying efficient patterns for deploying military units is critical to the speed and effectiveness of rescue operations. However, uncertainty in environmental conditions and field information can reduce the accuracy of efficiency measurement. This research proposes a DEA-based framework to evaluate and optimize the deployment of military units in humanitarian operations using bootstrap simulation. A three-stage DEA approach combined with a bootstrap method, grounded in natural, managerial, and free accessibility principles, is applied to data collected from active operational units in a real-world crisis response. Results indicate that under deterministic data only a subset of units is efficient, while many are classified as locationally inefficient. After generating simulated data and removing environmental noise, efficiencies are recalculated and comparative changes in unit performance are observed. These findings support more reliable decision-making and provide practical guidance for planners seeking robust, data-driven deployment strategies under uncertainty in complex humanitarian crisis environments.

کلیدواژه ها:

Data Envelopment Analysis ، Bootstrap ، humanitarian supply chain