Allocation Of Initial Attack Resources
Author(s)
D. B. Rideout, Y. Wei & A. Kirsch
Abstract
Increased scrutiny of federally funded programs combined with changes in fire
management reflects a demand for new fire program analysis tools. We
formulated an integer linear programming (ILP) model for initial attack resource
allocation that operates in a performance-based, cost-effectiveness analysis
(CEA) environment. The model optimizes the deployment of initial attack
resources for a user-defined set of fires that a manager would like to be prepared
for across alternative budget levels. The model also incorporates fire spread,
multiple ignitions, simultaneous ignitions and monitoring resources on a
landscape. It also evaluates the cost effectiveness of alternate fire fighting
resources and alternative pre-positioning locations. Fires that escape initial attack
are costly during the extended attack phase of fire management. To address this
within the scope of initial attack, we constructed and analyzed alternative
objective functions that incorporate a proxy for internalizing the cost of fires that
escape initial attack. This type of model can provide the basis for a wider scale
formulation with the potential to measure an organization’s performance and
promote a higher level of accountability and efficiency in fire programs.
Keywords: integer programming, initial attack, wildland fire, optimal
deployment.
1 Introduction
Wildland fire organizations, including US federal land management agencies,
customarily organize the suppression of unwanted fires into the three stages of
suppression: initial attack (IA), extended attack (EA) and large fire management.
Compartmentalizing this problem allows organizations to focus on the
functioning and funding of different stages of fire management. This enables the
analyst to focus with depth on the part of the problem of primary interest, but it
introduces the problem of potential \“spill over” effects that can be costly. For
Keywords
integer programming, initial attack, wildland fire, optimal
deployment
Related Book
Other papers in this volume
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