STORRE
STORRE: Stirling Online Research Repository
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1893/34357| Appears in Collections: | Computing Science and Mathematics Conference Papers and Proceedings |
| Author(s): | Lavinas, Yuri Aranha, Claus Ochoa, Gabriela |
| Contact Email: | goc@cs.stir.ac.uk |
| Title: | Search Trajectories Networks of Multiobjective Evolutionary Algorithms |
| Editor(s): | Jiménez Laredo, Juan Luis Hidalgo, J. Ignacio Babaagba, Kehinde Oluwatoyin |
| Citation: | Lavinas Y, Aranha C & Ochoa G (2022) Search Trajectories Networks of Multiobjective Evolutionary Algorithms. In: Jiménez Laredo JL, Hidalgo JI & Babaagba KO (eds.) Applications of Evolutionary Computation. Lecture Notes in Computer Science, 13224. EvoApplications 2022, Madrid, Spain, 20.04.2022-22.04.2022. Cham, Switzerland: Springer International Publishing, pp. 223-238. https://doi.org/10.1007/978-3-031-02462-7_15 |
| Issue Date: | 2022 |
| Date Deposited: | 24-May-2022 |
| Series/Report no.: | Lecture Notes in Computer Science, 13224 |
| Conference Name: | EvoApplications 2022 |
| Conference Dates: | 2022-04-20 - 2022-04-22 |
| Conference Location: | Madrid, Spain |
| Abstract: | Understanding the search dynamics of multiobjective evolutionary algorithms (MOEAs) is still an open problem. This paper extends a recent network-based tool, search trajectory networks (STNs), to model the behavior of MOEAs. Our approach uses the idea of decomposition, where a multiobjective problem is transformed into several single-objective problems. We show that STNs can be used to model and distinguish the search behavior of two popular multiobjective algorithms, MOEA/D and NSGA-II, using 10 continuous benchmark problems with 2 and 3 objectives. Our findings suggest that we can improve our understanding of MOEAs using STNs for algorithm analysis. |
| Status: | AM - Accepted Manuscript |
| Rights: | This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. This is a post-peer-review, pre-copyedit version of a paper published in Jiménez Laredo JL, Hidalgo JI & Babaagba KO (eds.) Applications of Evolutionary Computation. Lecture Notes in Computer Science, 13224. EvoApplications 2022, Madrid, Spain, 20.04.2022-22.04.2022. Cham, Switzerland: Springer International Publishing, pp. 223-238. The final authenticated version is available online at: https://doi.org/10.1007/978-3-031-02462-7_15 |
| Licence URL(s): | https://storre.stir.ac.uk/STORREEndUserLicence.pdf |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| EvoStar_2021_STNs.pdf | Fulltext - Accepted Version | 3.92 MB | Adobe PDF | View/Open |
This item is protected by original copyright |
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/
If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.