Planning habitat restoration with genetic algorithms

Brotánková, Jana, Urli, Tommaso, and Kilby, Philip (2016) Planning habitat restoration with genetic algorithms. In: Proceedings of the Genetic and Evolutionary Computation Conference. pp. 861-868. From: GECCO 16: Genetic and Evolutionary Computation Conference, 20-24 July 2016, Denver, CO, USA.

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Abstract

Conservation is an ethic of sustainable use of natural resources which focuses on the preservation of biodiversity. The term conservation planning encompasses the set of activities, typically carried out by conservation managers, that contribute to the attainment of this goal. Such activities can be preventive, such as the establishment of conservation reserves, or remedial, such as the displacement (or offsetting) of the species to be protected or the culling of invasive species. This last technique is often referred to as habitat restoration and, because of its lower impact on economic activities, is becoming more and more popular among conservation managers. In this paper we present the original formulation of the habitat restoration planning (HRP) problem, which captures some of the decisions and constraints faced by conservation managers in the context of habitat restoration. Example scenarios are drawn from the insular Great Barrier Reef (QLD) and Pilbara (WA) regions of Australia. In addition to the problem formulation, we describe an optimisation solver for the HRP, based on genetic algorithms (GAs), we discuss the preliminary results obtained by our solver, and we outline the current and future directions for the project.

Item ID: 49361
Item Type: Conference Item (Research - E1)
ISBN: 978-1-4503-4206-3
Keywords: combinatorial optimisation, conservation planning, genetic algorithms, habitat restoration, population dynamics
Date Deposited: 13 Jun 2017 01:53
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0802 Computation Theory and Mathematics > 080201 Analysis of Algorithms and Complexity @ 100%
SEO Codes: 96 ENVIRONMENT > 9605 Ecosystem Assessment and Management > 960599 Ecosystem Assessment and Management not elsewhere classified @ 100%
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