@article {bnh-3426, title = {An optimization model for aggregation of prescribed burn units}, journal = {TOP}, volume = {24}, year = {2016}, month = {04/2016}, pages = {180-195}, chapter = {180}, abstract = {

Fire is a natural component of many terrestrial ecosystems; however, uncontrolled intense wildfires can cause loss of human life and destruction of natural resources. Prescribed burning is a management activity undertaken for the purposes of both wildfire hazard reduction and the preservation of fire-adapted ecosystems. Achievement of prescribed burn targets is made difficult by operational constraints such as limited personnel, equipment and suitable weather for undertaking burning. Prescribed burn program implementation may benefit from efficiencies gained in undertaking larger burns. Here, we present a mixed-integer programming formulation for aggregation of prescribed burn units. The model minimizes the total prescribed burn perimeter requiring management, by aggregating existing {\textquoteleft}fundamental{\textquoteright} burn units into larger compact and contiguous units or {\textquoteleft}clusters{\textquoteright}. This problem is a special case of the {\textquoteleft}supervised regionalization{\textquoteright} or the {\textquoteleft}pp-regions problem{\textquoteright}. The model{\textquoteright}s functionality is demonstrated on a test landscape and a number of extensions and implementation issues are discussed.

}, doi = {10.1007/s11750-015-0383-y}, url = {https://link.springer.com/article/10.1007\%2Fs11750-015-0383-y}, author = {Minas, James P. and John Hearne} } @article {BF-3750, title = {An integrated optimization model for fuel management and fire suppression preparedness planning}, journal = {Annals of Operations Research}, year = {2013}, abstract = {Fuel management and suppression preparedness planning are elements of forest fire management that are strongly interrelated with one another. Despite this interrelation, previous forest fire management optimization models have tended to consider these components in isolation from one another. Here we present an integer programming model that incorporates both fuel management and suppression preparedness decisions, thus providing an integrated planning framework. A series of hypothetical test landscapes are used to demonstrate the model{\textquoteright}s functionality with easily interpretable results. A number of possible extensions to the model formulation are also discussed.}, issn = {0254-5330}, doi = {10.1007/s10479-012-1298-8}, author = {Minas, James P. and John Hearne and Martell, David} } @article {BF-3999, title = {A spatial optimisation model for multi-period landscape level fuel management to mitigate wildfire impacts}, journal = {European Journal of Operational Research}, year = {2013}, abstract = {Elevated fuel loads are contributing to an increase in the occurrence of, and area burned by, severe wildfires in many regions across the globe. In an attempt to reverse this trend, fire and land management agencies are investing in extensive fuel management programs. However, the planning of fuel treatment activities poses complicated decision-making problems with spatial and temporal dimensions. Here, we present a mixed integer programming model for spatially explicit multi-period scheduling of fuel treatments. The model provides a flexible framework that allows for landscape heterogeneity and a range of ecological and operational considerations and constraints. The model{\textquoteright}s functionality is demonstrated on a series of hypothetical test landscapes and a number of implementation issues are discussed.}, keywords = {Fuel management, Integer programming, OR in natural resources, Spatial optimization, Wildfire, wildland fire}, doi = {10.1016/j.ejor.2013.07.026}, url = {http://www.sciencedirect.com/science/article/pii/S0377221713006073}, author = {Minas, James P. and John Hearne and Martell, David} } @proceedings {BF-3046, title = {Integrated decision support model}, year = {2011}, month = {2011}, publisher = {Bushfire CRC}, address = {Sydney, Australia}, issn = {978-0-9806759-9-3}, url = {http://www.bushfirecrc.com/resources/pages-139-151-integrated-decision-support-model}, author = {Minas, James P. and John Hearne} } @article {BF-3132, title = {A review of operations research methods applicable to wildfire management}, journal = {International Journal of Wildland Fire}, year = {2011}, abstract = {Across the globe, wildfire-related destruction appears to be worsening despite increased fire suppression expenditure. At the same time, wildfire management is becoming increasingly complicated owing to factors such as an expanding wildland{\textendash}urban interface, interagency resource sharing and the recognition of the beneficial effects of fire on ecosystems. Operations research is the use of analytical techniques such as mathematical modelling to analyse interactions between people, resources and the environment to aid decision-making in complex systems. Fire managers operate in a highly challenging decision environment characterised by complexity, multiple conflicting objectives and uncertainty. We assert that some of these difficulties can be resolved with the use of operations research methods.Wepresent a range of operations research methods and discuss their applicability to wildfire management with illustrative examples drawn from the wildfire and disaster operations research literature.}, issn = {1049-8001}, doi = {10.1071/WF10129}, author = {Minas, James P. and John Hearne and John Handmer} }