Optimizing the ecological connectivity of landscapes with generalized flow models and preprocessing

TL;DR

This paper introduces a new generalized flow model and preprocessing algorithm to optimize ecological connectivity in landscapes, enabling larger problem instances to be solved efficiently and improving computational performance.

Contribution

The paper presents a novel generalized flow model and an efficient preprocessing method that enhance existing approaches for ecological connectivity optimization.

Findings

Preprocessing reduces graph size and improves computation times.

Larger problems can be solved with the new models and algorithms.

Greedy algorithms perform well in practice but poorly in worst-case scenarios.

Abstract

In this paper we consider the problem of optimizing the ecological connectivity of a landscape under a budget constraint by improving habitat areas and ecological corridors between them. We consider a formulation of this problem in terms of graphs in which vertices represent the habitat areas and arcs represent a probability of connection between two areas that depend on the quality of the respective corridor. We propose a new generalized flow model that improves existing models for this problem and an efficient preprocessing algorithm that reduces the size of the graphs on which generalized flows is computed. Reported numerical experiments highlight the benefice of these two contributions on computation times and show that larger problems can be solved using them. Our experiments also show that several variants of greedy algorithms perform relatively well on practical instances while they return arbitrary bad solutions in the worst case.