Abstract
Modeling ecological connectivity is an area of increasing interest amongst biologists and conservation agencies. In the past few years, different modeling approaches have been used by experts in the field to understand the state of wildlife distribution. One of these approaches is based on modeling land as a resistive network. The analysis of electric current in such networks allows biologists to understand how random walkers (animals) move across the landscape. In this paper we present a MIP model and a Local Search approach to tackle the problem of minimizing the effective resistance in an electrical network. This is then mapped onto landscapes in order to decide which areas need restoration to facilitate the movement of wildlife.
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Acknowledgements
We would like to thank Julian Di Stefano and Holly Sitters from the School of Ecosystems and Forest Sciences at the University of Melbourne as well as Nevil Amos from the Department of Environment, Land, Water and Planning of Victoria for meeting with us and introducing us to this problem.
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de Uña, D., Gange, G., Schachte, P., Stuckey, P.J. (2017). Minimizing Landscape Resistance for Habitat Conservation. In: Salvagnin, D., Lombardi, M. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2017. Lecture Notes in Computer Science(), vol 10335. Springer, Cham. https://doi.org/10.1007/978-3-319-59776-8_10
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