Title: Biogeography-based optimisation and ecological optimisation

Authors: Mourad Daoudi; Mohamed Ahmed-Nacer

Addresses: Electronics and Computer Science Faculty, Laboratory LSI, USTHB, BP 32 16111 El Alia, Bab-Ezzouar, Algiers, Algeria ' Electronics and Computer Science Faculty, Laboratory LSI, USTHB, BP 32 16111 El Alia, Bab-Ezzouar, Algiers, Algeria

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.

Keywords: NP-hard problems; metaheuristics; evolutionary algorithms; maximal covering species problem; MCSP; biogeography-based optimisation; BBO; harmony search; simulated annealing; reserve site selection; RSS; ecology; ecological optimisation; ecological conservation; species preservation; habitat preservation; combinatorial optimisation.

DOI: 10.1504/IJOR.2016.076883

International Journal of Operational Research, 2016 Vol.26 No.3, pp.308 - 322

Received: 07 Oct 2013
Accepted: 30 Apr 2014
Published online: 06 Jun 2016 *

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