A Computational Comparison of Evolutionary Algorithms for Water Resource Planning for Agricultural and Environmental Purposes

James Montgomery, Andrew Fitzgerald, Marcus Randall, Andrew Lewis

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

1 Citation (Scopus)
20 Downloads (Pure)

Abstract

The use of water resources for agricultural purposes, particularly in arid and semi-arid regions, is a matter of increasing concern across the world. Optimisation techniques can play an important role in improving the allocation of land to different crops, based on a utility function (such as net revenue) and the water resources needed to support these. Recent work proposed a model formulation for an agricultural region in the Murrumbidgee Irrigation Area of the Murray-Darling River basin in Australia, and found that the well-known NSGA-II technique could produce sensible crop mixes while preserving ground and surface water for environmental purposes. In the present study we apply Differential Evolution using two different solution representations, one of which explores the restricted space in which no land is left fallow. The results improve on those of the prior NSGA-II and demonstrate that a combination of solution representations allows Differential Evolution to more thoroughly explore the multiobjective space of profit versus environment.
Original languageEnglish
Title of host publication2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings
PublisherIEEE Computer Society
ISBN (Electronic) 978-1-5090-6017-7
DOIs
Publication statusPublished - 28 Sep 2018
EventIEEE World Congress on Computational Intelligence - Rio de Janeiro, Brazil
Duration: 8 Jul 201813 Jul 2018
Conference number: 2018
http://www.ecomp.poli.br/~wcci2018/

Conference

ConferenceIEEE World Congress on Computational Intelligence
Abbreviated titleIEEE WCCI 2018
CountryBrazil
CityRio de Janeiro
Period8/07/1813/07/18
Internet address

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water resource
crop
semiarid region
fallow
river basin
irrigation
surface water
groundwater
land
planning
comparison
world
allocation
profit

Cite this

Montgomery, J., Fitzgerald, A., Randall, M., & Lewis, A. (2018). A Computational Comparison of Evolutionary Algorithms for Water Resource Planning for Agricultural and Environmental Purposes. In 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings [8477712] IEEE Computer Society. https://doi.org/10.1109/CEC.2018.8477712
Montgomery, James ; Fitzgerald, Andrew ; Randall, Marcus ; Lewis, Andrew. / A Computational Comparison of Evolutionary Algorithms for Water Resource Planning for Agricultural and Environmental Purposes. 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings. IEEE Computer Society, 2018.
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Montgomery, J, Fitzgerald, A, Randall, M & Lewis, A 2018, A Computational Comparison of Evolutionary Algorithms for Water Resource Planning for Agricultural and Environmental Purposes. in 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings., 8477712, IEEE Computer Society, IEEE World Congress on Computational Intelligence , Rio de Janeiro, Brazil, 8/07/18. https://doi.org/10.1109/CEC.2018.8477712

A Computational Comparison of Evolutionary Algorithms for Water Resource Planning for Agricultural and Environmental Purposes. / Montgomery, James; Fitzgerald, Andrew; Randall, Marcus; Lewis, Andrew.

2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings. IEEE Computer Society, 2018. 8477712.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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Montgomery J, Fitzgerald A, Randall M, Lewis A. A Computational Comparison of Evolutionary Algorithms for Water Resource Planning for Agricultural and Environmental Purposes. In 2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings. IEEE Computer Society. 2018. 8477712 https://doi.org/10.1109/CEC.2018.8477712