ConsNet—A tabu search approach to the spatially coherent conservation area network design problem

Abstract

This paper presents a new approach to the solution of the well-studied conservation area network design problem (CANP), which is closely related to the classical set cover problem (SCP). The goal is to find the smallest amount of land that (when placed under conservation) will contain and protect a specified representation level of biodiversity resources. A new tabu search methodology is applied to an extension of the "basic" CANP which explicitly considers additional spatial requirements for improved conservation planning. The underlying search engine, modular adaptive self-learning tabu search (MASTS), incorporates state-of-the-art techniques including adaptive tabu search, dynamic neighborhood selection, and rule-based objectives. The ability to utilize intransitive orderings within a rule-based objective gives the search flexibility, improving solution quality while saving computation. This paper demonstrates how rule-based objectives can be used to design near optimal conservation area networks in which the individual conservation areas are well connected. The results represent a considerable improvement over classical techniques that do not consider spatial features. This paper provides an initial description of ConsNet, a comprehensive software package for systematic conservation planning.

Multi-objective optimization in systematic conservation planning and the representation of genetic variability among populations

“…However, when 2 criteria represent different value systems, it may be impossible to combine such criteria in a meaningful way (e.g., comparing the preservation of endangered species and the promotion of economic development). A single objective function can result in the association of utterly disparate elements, requiring assumptions that decision-makers may consider inadequate and even leading to inaccurate results (Ciarleglio et al, 2010). This prompted us to use a multi-objective approach for solving SCP.…”

“…However, it is worth noting that this technique does not guarantee optimal solutions. The mainly metaheuristics used for SCP include simulated annealing [SPEXAN (Ball, 2000), SITES (Possingham et al, 2000), and Marxan (Ardron et al, 2010)], as well as the tabu search [ConsNet (Ciarleglio, 2010)]. (Underhill, 1994;Arthur et al, 1997) X C-Plan (Pressey et al, 1996) Tiebreak criterion (rarity, frequency).…”

Using Advanced Tabu Search Approaches to Perform Enhanced Air Mobility Command Operational Airlift Analyses

“…This highly innovative research employed both pure TS and a hybrid mathematical programming-TS approach to the aircraft grounding problem and to the reduced airport capacity problem to achieve superior results in both cases. While Kinney [8] and Kinney et al [20] also used a hybrid methodology, the problems approached by Yang were considerably more restrictive in the context of the associated constraints.The research documented in Ciarleglio [3] and Ciarleglio et al [22,23] constitute a major breakthrough and departure from previous work in TS. This research resulted in a fundamental reusable framework, the modular adaptive self learning TS (MASTS) for the application of advanced TS techniques.…”

“…The research documented in Ciarleglio [3] and Ciarleglio et al [22,23] constitute a major breakthrough and departure from previous work in TS. This research resulted in a fundamental reusable framework, the modular adaptive self learning TS (MASTS) for the application of advanced TS techniques.…”

“…Not only does MASTS embody good design practices, it also includes some highly desirable innovations such as Rule Based Objectives (RBOs) and Dynamic Neighborhood Selection (DNS) that aid greatly to its strength. Initial applications of MASTS to exceptionally challenging problems such as Ground Water Management and Species Conservation [22,23] have produced unprecedented successes and have established MASTS at the forefront of direct search methodologies.…”