Introductory overview

Title

Introductory overview: Optimization using evolutionary algorithms and other metaheuristics

 Author

Maier, H. R. (University of Adelaide)
Razavi, S. (University of Saskatchewan)
Kapelan, Z. (TU Delft Sanitary Engineering; University of Exeter) ORCID 0000-0002-0934-4470
Matott, L. S. (University at Buffalo, State University of New York)
Kasprzyk, J. (University of Colorado)
Tolson, B. A. (University of Waterloo)

Date

2019

 Abstract

Environmental models are used extensively to evaluate the effectiveness of a range of design, planning, operational, management and policy options. However, the number of options that can be evaluated manually is generally limited, making it difficult to identify the most suitable options to consider in decision-making processes. By linking environmental models with evolutionary and other metaheuristic optimization algorithms, the decision options that make best use of scarce resources, achieve the best environmental outcomes for a given budget or provide the best trade-offs between competing objectives can be identified. This Introductory Overview presents reasons for embedding formal optimization approaches in environmental decision-making processes, details how environmental problems are formulated as optimization problems and outlines how single- and multi-objective optimization approaches find good solutions to environmental problems. Practical guidance and potential challenges are also provided.

 To reference this document use:

http://resolver.tudelft.nl/uuid:fb33b6b1-4ab7-4b57-a3fd-d34127b5f843

 DOI

https://doi.org/10.1016/j.envsoft.2018.11.018

 Embargo date

2021-02-05

 ISSN

1364-8152

 Source

Environmental Modelling & Software, 114, 195-213

 Bibliographical note

Accepted Author Manuscript

 Part of collection

Institutional Repository

 Document type

review

 Rights

© 2019 H. R. Maier, S. Razavi, Z. Kapelan, L. S. Matott, J. Kasprzyk, B. A. Tolson
Files
PDF Kapelan_EMS_Paper.pdf 2.67 MB
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