Optimization Based Decision Support Tools for Fire and Rescue Resource Planning

When accidents occur, it is essential that fire and rescue service respond quickly and efficiently to the accident site to reduce suffering and save lives and property. Planning and coordinating of fire and rescue resources is therefore important in order to maintain a safe society. Firefighters in Sweden have by tradition worked in teams of five, and they have been allocated to fire stations strategically located in populated areas. However, this working approach has recently started to change and the fire and rescue services have started to deploy smaller groups of firefighters. These smaller units can be, for example, strategically located near high-risk areas or roads, or used for preventive work. The complexity of the resource planning process thus increases since the decision makers have to keep track of a large number of small units spread over the area. The new way of working has resulted in an increased need of support tools that can help the fire and rescue services in decisions regarding the resource management. In this thesis, optimization based decision support tools are developed in order to to support the fire and rescue service so they can efficiently manage, coordinate and dispatch fire and rescue resources with respect to the present demand for service. To find appropriate strategic and tactical locations for different types of response units, an optimization model that minimizes the response time to expected accidents is developed. The model considers both the response time for the first responding unit as well as the response time for the last responding unit. Furthermore, the model is flexible enough to incorporate any type of accidents or resources. The results show that the model can be used to produce practical support for various types of location decisions. To support the more complex operational planning, three optimization based decision support tools are developed. The tools can help the fire and rescue service to always maintain an adequate level of preparedness for handling accidents. To evaluate the preparedness, a quantitative measure has been defined and serves as the basis for the tools. The first tool can help illustrate the preparedness, the second tool to select appropriate vehicles and firefighters to dispatch to accidents, and the third tool to suggest how resources can be relocated to maintain an adequate preparedness for new accidents. The developed decision support tools are evaluated through tests and experiments with fire and rescue services in Sweden. Results from the experiments indicate that the three tools can support the fire and rescue service in operational decisions and in maintaining an adequate preparedness for handling accidents, but also that the planning time seems to increase when using the support tools. However, the participants’ experiences of the tools were in general positive, and they thought the tools were useful and that the tools could support their daily work. The perception of preparedness, which usually varies quite a bit among individuals, also seems to become more uniform with access to the tools