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Heuristic and Approximate Optimization Methods for Spatial Conservation Prioritization
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DOI：10.1093/oso/9780199547760.003.0005.png)
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Abstract
This chapter discusses optimization techniques that can be applied to the solution of the conservation resource allocation problem (Chapters 1 and 3), some variants of which exhibit characteristics that make the problem unsuitable or impractical for solution using exact optimization methods (Chapter 4). Such characteristics include non-linear objectives or constraints, problems that are large (many planning units and/or feature constraints), spatially non-linear formulations, dynamic feedback mechanisms in the system model, or any form of stochastic dynamics. For example, a species-specific extinction probability could be derived from a complex stochastic non-linear process (e.g. PVA model, Chapter 9) that includes a complex relationship between landscape characteristics and life-history parameters. Such a problem is not amenable for analysis using exact optimization methods. In this chapter we review heuristic and approximate optimization methods that can be applied to practically any spatial conservation prioritization problem. These algorithms can be found in the literature under different names, including site selection algorithms, reserve selection algorithms, reserve network design, spatial optimization, and conservation prioritization.
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