A response-aware risk management framework for search-and-rescue operations

Efficient coordination among all assets participating in a response to a search-and-rescue (SAR) incident has long been a focus of many governments and organizations. Finding innovative solutions that guarantee a swift reaction to the distressed entity with a rational use of the available resources is pivotal to the success of the SAR operation. In spite of the plethora of successfully deployed SAR systems, we witness a substantial gap when it comes to the integration of risk-driven analyses into the underlying machinery of any decision support platform that leans upon the in-field SAR assets. This paper extends a recently proposed risk management framework [1] by adding automated modules for risk monitoring and response selection. An evolutionary multi-objective optimization algorithm is used to navigate across the discrete space of all available assets and their set of actions in order to present a limited number of promising responses to a SAR operator, who will ultimately decide what action must be carried out. The proposed methodology was validated in the context of a simulated nautical SAR scenario in the Canadian Atlantic coastline with nine different types of ground, maritime and aerial assets.