A modified matrix adaptation evolution strategy with restarts for constrained real-world problems
- In combination with successful constraint handling techniques, a Matrix Adaptation Evolution Strategy (MA-ES) variant (the εMAg-ES) turned out to be a competitive algorithm on the constrained optimization problems proposed for the CEC 2018 competition on constrained single objective real-parameter optimization. A subsequent analysis points to additional potential in terms of robustness and solution quality. The consideration of a restart scheme and adjustments in the constraint handling techniques put this into effect and simplify the configuration. The resulting BP-εMAg-ES algorithm is applied to the constrained problems proposed for the IEEE CEC 2020 competition on Real-World Single-Objective Constrained optimization. The novel MA-ES variant realizes improvements over the original εMAg-ES in terms of feasibility and effectiveness on many of the real-world benchmarks. The BP-εMAg-ES realizes a feasibility rate of 100% on 44 out of 57 real-world problems and improves the best-known solution in 5 cases.
Author: | Michael HellwigORCiD, Hans-Georg BeyerORCiD |
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DOI: | https://doi.org/10.1109/CEC48606.2020.9185566 |
ISBN: | 978-1-7281-6929-3 |
Parent Title (English): | 2020 IEEE Congress on Evolutionary Computation (CEC) |
Publisher: | IEEE |
Place of publication: | Piscataway, NJ |
Document Type: | Conference Proceeding |
Language: | English |
Year of publication: | 2020 |
Release Date: | 2020/12/01 |
Tag: | Constraints; Evolutionary algorithms; Optimization |
Number of pages: | 8 |
Organisationseinheit: | Technik / Department of Computer Science (Ende 2021 aufgelöst; Integration in die übergeordnete OE Technik) |
Forschung / Forschungszentrum Business Informatics | |
Technik / Technik | Engineering & Technology | |
DDC classes: | 000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik |
Open Access?: | nein |
Publicationlist: | Beyer, Hans-Georg |
Hellwig, Michael |