A novel non-redundant path method for the maximum covering species problem with connection requirements

This paper proposes a novel model formulation for the Maximum Covering Species Problem that incorporates spatial connectivity requirements. This model, called the Connected Maximum Covering Species Problem, enforces structural connectivity and relies on knowledge of induced paths, or what we call non-redundant paths in conservation planning. A tabu-search-based algorithm is proposed to list all non-redundant paths, which then serve as input to the Connected Maximum Covering Species Problem. Since this approach relies on path-related input data, it offers several advantages over other approaches in this area of research, such as heuristic adaptation or embedding in time-dynamic concepts. Linearization aspects of the novel model formulation are discussed and the strength of the proposed approach in conservation planning is demonstrated in a computational study.