Beschreibung:
<jats:p> Wildlife corridors are often used to connect critical habitat for species protection. Mixed integer programming models have been used in the past to create wildlife corridors, but they lack the capacity to control corridor geometry. We propose an approach that employs path planning techniques from artificial intelligence to account for and control corridor geometry, such as width and length. By combining path planning with network optimization, our approach allows the user to control and optimize the geometric characteristics of wildlife corridors. We illustrate our approach on two realistic landscapes and present numerical results on several computer-generated landscapes. The computational results indicate that this approach is efficient and can address problems controlling corridor geometry that were previously thought intractable. The approach has potential applications in such areas as the selection of routes or barrier construction problems, an example of which is firebreak design. </jats:p><jats:p> Data are available at https://doi.org/10.1287/opre.2018.1758 . </jats:p>