Linear optimization for ecological indices based on aggregation functions

Gleb Beliakov; Andrew Geschke; Simon James; Dale Nimmo

doi:10.1007/978-3-319-40581-0_33

Linear optimization for ecological indices based on aggregation functions

Gleb Beliakov, Andrew Geschke, Simon James, Dale Nimmo

Agricultural, Environmental and Veterinary Sciences

Deakin University

Research output: Book chapter/Published conference paper › Conference paper › peer-review

2 Citations (Scopus)

Abstract

We consider an optimization problem in ecology where our objective is to maximize biodiversity with respect to different land-use allocations. As it turns out, the main problem can be framed as learning the weights of a weighted arithmetic mean where the objective is the geometric mean of its outputs. We propose methods for approximating solutions to this and similar problems, which are non-linear by nature, using linear and bilevel techniques.

Original language	English
Title of host publication	Information processing and management of uncertainty in knowledge-based systems
Subtitle of host publication	16th International confernce, IPMU
Editors	Joao Paulo Carvalho, Marie-Jeanne Lesot, Uzay Kaymak, Susana Vieira, Bernadette Bouchon-Meunier, Ronald R. Yager
Place of Publication	Switzerland
Publisher	Springer-Verlag London Ltd.
Pages	411-422
Number of pages	12
Volume	611
ISBN (Electronic)	9783319405810
ISBN (Print)	9783319405803
DOIs	https://doi.org/10.1007/978-3-319-40581-0_33
Publication status	Published - 2016
Event	16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems: IPMU 2016 - Eindhoven University of Technology , Eindhoven, Netherlands Duration: 20 Jun 2016 → 24 Jun 2016 http://is.ieis.tue.nl/ipmu/

Publication series

Name	Communications in Computer and Information Science
Volume	611
ISSN (Print)	1865-0929

Conference

Conference	16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems
Country/Territory	Netherlands
City	Eindhoven
Period	20/06/16 → 24/06/16
Internet address	http://is.ieis.tue.nl/ipmu/

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10.1007/978-3-319-40581-0_33

Cite this

Beliakov, G., Geschke, A., James, S., & Nimmo, D. (2016). Linear optimization for ecological indices based on aggregation functions. In J. P. Carvalho, M.-J. Lesot, U. Kaymak, S. Vieira, B. Bouchon-Meunier, & R. R. Yager (Eds.), Information processing and management of uncertainty in knowledge-based systems: 16th International confernce, IPMU (Vol. 611, pp. 411-422). (Communications in Computer and Information Science; Vol. 611). Springer-Verlag London Ltd.. https://doi.org/10.1007/978-3-319-40581-0_33

Beliakov, Gleb ; Geschke, Andrew ; James, Simon et al. / Linear optimization for ecological indices based on aggregation functions. Information processing and management of uncertainty in knowledge-based systems: 16th International confernce, IPMU. editor / Joao Paulo Carvalho ; Marie-Jeanne Lesot ; Uzay Kaymak ; Susana Vieira ; Bernadette Bouchon-Meunier ; Ronald R. Yager. Vol. 611 Switzerland : Springer-Verlag London Ltd., 2016. pp. 411-422 (Communications in Computer and Information Science).

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title = "Linear optimization for ecological indices based on aggregation functions",

abstract = "We consider an optimization problem in ecology where our objective is to maximize biodiversity with respect to different land-use allocations. As it turns out, the main problem can be framed as learning the weights of a weighted arithmetic mean where the objective is the geometric mean of its outputs. We propose methods for approximating solutions to this and similar problems, which are non-linear by nature, using linear and bilevel techniques.",

keywords = "Aggregation functions, Biodiversity, Ecology, Linear programming, Weight learning",

author = "Gleb Beliakov and Andrew Geschke and Simon James and Dale Nimmo",

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booktitle = "Information processing and management of uncertainty in knowledge-based systems",

address = "Germany",

note = "16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems : IPMU 2016 ; Conference date: 20-06-2016 Through 24-06-2016",

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Beliakov, G, Geschke, A, James, S & Nimmo, D 2016, Linear optimization for ecological indices based on aggregation functions. in JP Carvalho, M-J Lesot, U Kaymak, S Vieira, B Bouchon-Meunier & RR Yager (eds), Information processing and management of uncertainty in knowledge-based systems: 16th International confernce, IPMU. vol. 611, Communications in Computer and Information Science, vol. 611, Springer-Verlag London Ltd., Switzerland, pp. 411-422, 16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Eindhoven, Netherlands, 20/06/16. https://doi.org/10.1007/978-3-319-40581-0_33

Linear optimization for ecological indices based on aggregation functions. / Beliakov, Gleb; Geschke, Andrew; James, Simon et al.
Information processing and management of uncertainty in knowledge-based systems: 16th International confernce, IPMU. ed. / Joao Paulo Carvalho; Marie-Jeanne Lesot; Uzay Kaymak; Susana Vieira; Bernadette Bouchon-Meunier; Ronald R. Yager. Vol. 611 Switzerland: Springer-Verlag London Ltd., 2016. p. 411-422 (Communications in Computer and Information Science; Vol. 611).

Research output: Book chapter/Published conference paper › Conference paper › peer-review

TY - GEN

T1 - Linear optimization for ecological indices based on aggregation functions

AU - Beliakov, Gleb

AU - Geschke, Andrew

AU - James, Simon

AU - Nimmo, Dale

PY - 2016

Y1 - 2016

N2 - We consider an optimization problem in ecology where our objective is to maximize biodiversity with respect to different land-use allocations. As it turns out, the main problem can be framed as learning the weights of a weighted arithmetic mean where the objective is the geometric mean of its outputs. We propose methods for approximating solutions to this and similar problems, which are non-linear by nature, using linear and bilevel techniques.

AB - We consider an optimization problem in ecology where our objective is to maximize biodiversity with respect to different land-use allocations. As it turns out, the main problem can be framed as learning the weights of a weighted arithmetic mean where the objective is the geometric mean of its outputs. We propose methods for approximating solutions to this and similar problems, which are non-linear by nature, using linear and bilevel techniques.

KW - Aggregation functions

KW - Biodiversity

KW - Ecology

KW - Linear programming

KW - Weight learning

UR - https://www.scopus.com/pages/publications/84977177233

U2 - 10.1007/978-3-319-40581-0_33

DO - 10.1007/978-3-319-40581-0_33

M3 - Conference paper

AN - SCOPUS:84977177233

SN - 9783319405803

VL - 611

T3 - Communications in Computer and Information Science

SP - 411

EP - 422

BT - Information processing and management of uncertainty in knowledge-based systems

A2 - Carvalho, Joao Paulo

A2 - Lesot, Marie-Jeanne

A2 - Kaymak, Uzay

A2 - Vieira, Susana

A2 - Bouchon-Meunier, Bernadette

A2 - Yager, Ronald R.

PB - Springer-Verlag London Ltd.

CY - Switzerland

T2 - 16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems

Y2 - 20 June 2016 through 24 June 2016

ER -

Beliakov G, Geschke A, James S, Nimmo D. Linear optimization for ecological indices based on aggregation functions. In Carvalho JP, Lesot MJ, Kaymak U, Vieira S, Bouchon-Meunier B, Yager RR, editors, Information processing and management of uncertainty in knowledge-based systems: 16th International confernce, IPMU. Vol. 611. Switzerland: Springer-Verlag London Ltd. 2016. p. 411-422. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-40581-0_33

Linear optimization for ecological indices based on aggregation functions

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