Unifying reserve design strategies with graph theory and constraint programming
The delineation of areas of high ecological or biodiversity value is a priority of any conservation program. However, the selection of optimal areas to be preserved necessarily results from a compromise between the complexity of ecological processes and managers' constraints. Current reserve design models usually focus on few criteria, which often leads to an oversimplification of the underlying conservation issues. This paper shows that Constraint Programming (CP) can be the basis of a more unified, flexible and extensible framework. First, the reserve design problem is formalized. Secondly, the problem is modeled from two different angles by using two graph-based models. Then CP is used to aggregate those models through a unique Constraint Satisfaction Problem. Our model is finally evaluated on a real use case addressing the problem of rainforest fragmentation in New Caledonia, a biodiversity hotspot. Results are promising and highlight challenging perspectives to overtake in future work.
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dig-cirad-fr-5964082021-04-29T11:45:47Z http://agritrop.cirad.fr/596408/ http://agritrop.cirad.fr/596408/ Unifying reserve design strategies with graph theory and constraint programming. Justeau-Allaire Dimitri, Birnbaum Philippe, Lorca Xavier. 2018. In : Principles and practice of constraint programming: 24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings. Hooker John (ed.). Cham : Springer, 507-523. (Lecture Notes in Computer Science, 11008) ISBN 978-3-319-98333-2 International Conference on Principles and Practice of Constraint Programming. 24, Lille, France, 27 Août 2018/31 Août 2018.https://doi.org/10.1007/978-3-319-98334-9_33 <https://doi.org/10.1007/978-3-319-98334-9_33> Researchers Unifying reserve design strategies with graph theory and constraint programming Justeau-Allaire, Dimitri Birnbaum, Philippe Lorca, Xavier eng 2018 Springer Principles and practice of constraint programming: 24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings The delineation of areas of high ecological or biodiversity value is a priority of any conservation program. However, the selection of optimal areas to be preserved necessarily results from a compromise between the complexity of ecological processes and managers' constraints. Current reserve design models usually focus on few criteria, which often leads to an oversimplification of the underlying conservation issues. This paper shows that Constraint Programming (CP) can be the basis of a more unified, flexible and extensible framework. First, the reserve design problem is formalized. Secondly, the problem is modeled from two different angles by using two graph-based models. Then CP is used to aggregate those models through a unique Constraint Satisfaction Problem. Our model is finally evaluated on a real use case addressing the problem of rainforest fragmentation in New Caledonia, a biodiversity hotspot. Results are promising and highlight challenging perspectives to overtake in future work. conference_item info:eu-repo/semantics/conferenceObject Conference info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/596408/1/596408.pdf text Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1007/978-3-319-98334-9_33 10.1007/978-3-319-98334-9_33 https://catalogue-bibliotheques.cirad.fr/cgi-bin/koha/opac-detail.pl?biblionumber=220778 info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-319-98334-9_33 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1007/978-3-319-98334-9_33 |
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The delineation of areas of high ecological or biodiversity value is a priority of any conservation program. However, the selection of optimal areas to be preserved necessarily results from a compromise between the complexity of ecological processes and managers' constraints. Current reserve design models usually focus on few criteria, which often leads to an oversimplification of the underlying conservation issues. This paper shows that Constraint Programming (CP) can be the basis of a more unified, flexible and extensible framework. First, the reserve design problem is formalized. Secondly, the problem is modeled from two different angles by using two graph-based models. Then CP is used to aggregate those models through a unique Constraint Satisfaction Problem. Our model is finally evaluated on a real use case addressing the problem of rainforest fragmentation in New Caledonia, a biodiversity hotspot. Results are promising and highlight challenging perspectives to overtake in future work. |
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Justeau-Allaire, Dimitri Birnbaum, Philippe Lorca, Xavier |
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Justeau-Allaire, Dimitri Birnbaum, Philippe Lorca, Xavier Unifying reserve design strategies with graph theory and constraint programming |
author_facet |
Justeau-Allaire, Dimitri Birnbaum, Philippe Lorca, Xavier |
author_sort |
Justeau-Allaire, Dimitri |
title |
Unifying reserve design strategies with graph theory and constraint programming |
title_short |
Unifying reserve design strategies with graph theory and constraint programming |
title_full |
Unifying reserve design strategies with graph theory and constraint programming |
title_fullStr |
Unifying reserve design strategies with graph theory and constraint programming |
title_full_unstemmed |
Unifying reserve design strategies with graph theory and constraint programming |
title_sort |
unifying reserve design strategies with graph theory and constraint programming |
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Springer |
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http://agritrop.cirad.fr/596408/ http://agritrop.cirad.fr/596408/1/596408.pdf |
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AT justeauallairedimitri unifyingreservedesignstrategieswithgraphtheoryandconstraintprogramming AT birnbaumphilippe unifyingreservedesignstrategieswithgraphtheoryandconstraintprogramming AT lorcaxavier unifyingreservedesignstrategieswithgraphtheoryandconstraintprogramming |
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1758026623670550528 |