Multi-Objective Decision Making for the Fire & Rescue Services - A Scoping Study

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This proposal directly addresses research issues relating to the strategic management of the Fire and Rescue Services (FRS). More specifically it is a scoping bid to determine whether or not Evolutionary Algorithms (EA) can be used to find high performance strategies for a Fire Brigade's deployment of resources to minimise the risk of the loss of life and property. EA are essentially a class of algorithms which are able to cope with challenging, complex problems that cannot be solved by classical optimization and search methods. They have the advantage that they do not need the well defined objective function that is required by other algorithms. Also the cope with conflicting constraints, multi-objective search spaces and other hazards such as discrete variables and non-linearity.The bid arises from the participation by Miles & Rezgui in a joint EPSRC/CLG sandpit to look at research ideas for Integrated Risk Management Planning (IRMP) for the FRS. A scoping bid, with limited research aims, was suggested by the sandpit mentors because they felt that there is a risk that the technology might not be able to cope with the problem domain. The scoping bid will therefore enable the applicants and the sandpit mentors to assess whether or not the proposed strategy can cope with the domain complexity to produce sensible, high performance solutions. This work will be undertaken in collaboration the Building Research Establishment (BRE) and with the Fire and Resilience Directorate of CLG to ensure that the work is relevant to the needs of FRSs. BRE's role is to provide fire engineering expertise.