Duro, J.A., Yan, Y., Giagkiozis, I. et al. (9 more authors) (2021) Liger : a cross-platform open-source integrated optimization and decision-making environment. Applied Soft Computing, 98. 106851. ISSN 1568-4946
Abstract
Real-world optimization problems involving multiple conflicting objectives are commonly best solved using multi-objective optimization as this provides decision-makers with a family of trade-off solutions. However, the complexity of using multi-objective optimization algorithms often impedes the optimization process. Knowing which optimization algorithm is the most suitable for the given problem, or even which setup parameters to pick, requires someone to be an optimization specialist. The lack of supporting software that is readily available, easy to use and transparent can lead to increased design times and increased cost. To address these challenges, Liger is presented. Liger has been designed for ease of use in industry by non-specialists in optimization. The user interacts with Liger via a visual programming language to create an optimization workflow, enabling the user to solve an optimization problem. Liger contains a novel optimization library known as Tigon. The library utilizes the concept of design patterns to enable the composition of optimization algorithms by making use of simple reusable operator nodes. The library offers a varied range of multi-objective evolutionary algorithms which cover different paradigms in evolutionary computation; and supports a wide variety of problem types, including support for using more than one programming language at a time to implement the optimization model. Additionally, Liger functionality can be easily extended by plugins that provide access to state-of-the-art visualization tools and are responsible for managing the graphical user interface. Lastly, new user-driven interactive capabilities are shown to facilitate the decision-making process and are demonstrated on a control engineering optimization problem.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Software engineering; Multi-objective optimization; Multi-criteria decision-making; Evolutionary algorithms; Metaheuristics |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number European Commission - FP6/FP7 NH-MCDM - 295152 Engineering and Physical Sciences Research Council EP/M506618/1; EP/L025760/1 Innovate UK (TSB) 78938-506185 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 Nov 2020 14:14 |
Last Modified: | 04 Feb 2022 12:08 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.asoc.2020.106851 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:168219 |