Paper Info
Title
Using a multi-objective artificial immune system approach for biodiversity conservation
Abstract
A key issue in policies for sustainable development is related to biodiversity conservation, which aim is to minimize the costs of conservation while ensuring the maximal biodiversity representation, a NP-hard problem. We propose the use of a constrained multi-objective artificial immune system algorithm (MAIS), based on principles of systematic conservation planning (SCP), incorporating allelic and habitat information to deal with the biodiversity conservation problem. As a case study, we used an Eugenia dysenterica data set. We were able to identify the best set of populations that should be protected to preserve the species diversity. The proposed approach can be used to help construct in situ conservation schemes with maximal genetic richness, and also be extended to ex situ conservation. This is the first time that an artificial immune system algorithm is applied to the SCP problem using genetic and habitat information as well.
Year
DOI
Venue
2017
10.1109/FSKD.2017.8392911
2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)
Keywords
Field
DocType
multi-objective optimization,artificial immune systems,systematic conservation planning,biodiversity conservation,sustainability
Biodiversity,Mathematical optimization,Artificial immune system,Species richness,Habitat,In situ conservation,Environmental resource management,Computer science,Conservation planning,Sustainable development,Ex situ conservation
Conference
ISBN
Citations 
PageRank 
978-1-5386-2166-0
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Shana Schlottfeldt111.38
Maria Emilia M. T. Walter23714.23
André Carlos Ponce Leon Ferreira de Carvalho3102391.35
Mariana P. C. Telles401.01
José Alexandre Felizola Diniz-Filho5243.95