Geometric optimization of wildlife corridors on grid-based landscapes using integer programming

Abstract

Conservation corridors play a critical role in mitigating biodiversity loss by linking fragmented habitats. A central challenge in designing these corridors lies in satisfying ecological requirements through geometric constraints such as connectivity, redundancy, width, and size. In this study, we propose a mixed-integer programming model that integrates these geometric features into the corridor design process, with the objective of maximizing corridor utility over a grid-based landscape. To enhance computational performance, we develop a Branch-and-Cut algorithm supported by a bound-improving heuristic, valid inequalities, and a variable reduction preprocessing routine. We evaluate our approach on a real-world landscape aimed at protecting the Florida panther, as well as on a suite of computer-generated landscapes. Results show that the algorithm can efficiently produce near-optimal solutions for instances with up to 3000 patches within a two-hour time limit.