An Innovative What-If Optimization Strategy for Fleet Assets Allocation in Emergency Situations

In this work, an innovative decision support system for the strategic selection and dispatch of assets during emergency situations is presented. The proposed methodology employs a multi-objective optimization framework, taking into account factors such as cost, utility, readiness, efficiency, and the capabilities of the selected assets in relation to the specific emergency scenario. Additionally, the optimization includes a risk (what-if) analysis to enhance the solutions resilience in the case of concurrent emergencies. The experimental validation against real-world use-cases, including human operators' selection, has preliminarily demonstrated the efficiency and reliability of the proposed optimization strategy.