Evolutionary optimization strategies applied to wireless fleet management in emergency scenarios

In this paper, the use of evolutionary metaheuristic for the management of emergency rescue operations applied to real-word scenarios is analyzed. The problem of selecting the best candidate assets for a given emergency event is addressed. While the problem of deploying one single resource is trivial, its complexity grows when considering more assets to be deployed at the same time. Two objective functions (utility and cost) have been defined and are estimated against features of candidate assets and input event. The full Pareto front of estimated solutions is presented to operators through an interactive tool for supporting the decision making process. The prototype is under validation at the headquarter of the Centrale Unica Emergenza (CUE) of Trento, Italy.

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