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A computational comparison of evolutionary algorithms for water resource planning for agricultural and environmental purposes


Montgomery, J and Fitzgerald, A and Randall, M and Lewis, A, A computational comparison of evolutionary algorithms for water resource planning for agricultural and environmental purposes, 2018 IEEE Congress on Evolutionary Computation, 8-13 July 2018, Rio de Janeiro, Brazil, pp. 1-8. ISBN 9781509060177 (2018) [Refereed Conference Paper]

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Copyright 2018 IEEE

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DOI: doi:10.1109/CEC.2018.8477712


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.

Item Details

Item Type:Refereed Conference Paper
Keywords:water resource management, crop planning, differential evolution, NSGA-II
Research Division:Information and Computing Sciences
Research Group:Machine learning
Research Field:Neural networks
Objective Division:Environmental Management
Objective Group:Terrestrial systems and management
Objective Field:Terrestrial systems and management not elsewhere classified
UTAS Author:Montgomery, J (Dr James Montgomery)
ID Code:125541
Year Published:2018
Web of Science® Times Cited:2
Deposited By:Information and Communication Technology
Deposited On:2018-04-23
Last Modified:2019-02-25
Downloads:115 View Download Statistics

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