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Robust temporal optimisation for a crop planning problem under climate change uncertainty


Randall, M and Montgomery, EJ and Lewis, A, Robust temporal optimisation for a crop planning problem under climate change uncertainty, Operations Research Perspectives, 9 Article 100219. ISSN 2214-7160 (2022) [Refereed Article]

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2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (

DOI: doi:10.1016/j.orp.2021.100219


Considering a temporal dimension allows for the delivery of rolling solutions to complex real-world problems. Moving forward in time brings uncertainty, and large margins for potential error in solutions. For the multi-year crop planning problem, the largest uncertainty is how the climate will change over coming decades. The innovation this paper presents are novel methods that allow the solver to produce feasible solutions under all climate models tested, simultaneously. Three new measures of robustness are introduced and evaluated. The highly robust solutions are shown to vary little across different climate change projections, maintaining consistent net revenue and environmental flow deficits.

Item Details

Item Type:Refereed Article
Keywords:robust optimisation, climate change, crop planning, deep uncertainty
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Evolutionary computation
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the information and computing sciences
UTAS Author:Montgomery, EJ (Dr James Montgomery)
ID Code:148432
Year Published:2022
Deposited By:Information and Communication Technology
Deposited On:2022-01-10
Last Modified:2022-03-10
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