Biogeography-based optimisation and ecological optimisation

Biogeography-based optimisation and ecological optimisation

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Article ID: iaor20162715
Volume: 26
Issue: 3
Start Page Number: 308
End Page Number: 322
Publication Date: Jun 2016
Journal: International Journal of Operational Research
Authors: ,
Keywords: ecology, biology, heuristics, combinatorial optimization, geography & environment
Abstract:

The ecological conservation problem for preserving species and their habitats was formulated as an optimisation problem of maximal covering species problem in order to find the maximal number of species while limiting the number of selected sites. It is a combinatorial optimisation problem NP‐hard, and thus intractable with classical methods when data is very large. Metaheuristics offer an alternative to solve this type of problems. In this context, we consider a recently‐developed metaheuristic, 'biogeography‐based optimisation', well suited for constrained problems. The testbed is an Oregon terrestrial vertebrate data set composed of 426 species and 441 sites. Results show the competitiveness of the proposed method with other metaheuristic approaches in the literature like harmony search metaheuristic.

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