Multi-population inflationary differential evolution algorithm with adaptive local restart
Di Carlo, Marilena and Vasile, Massimiliano and Minisci, Edmondo; (2015) Multi-population inflationary differential evolution algorithm with adaptive local restart. In: 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., JPN, pp. 632-639. ISBN 9781479974924 (https://doi.org/10.1109/CEC.2015.7256950)
Preview |
Text.
Filename: Di_Carlo_etal_CEC2015_Multi_population_inflationary_differential_evolution_algorithm_adaptive_local_restart.pdf
Accepted Author Manuscript Download (128kB)| Preview |
Abstract
In this paper a Multi-Population Inflationary Differential Evolution algorithm with Adaptive Local Restart is presented and extensively tested over more than fifty test functions from the CEC 2005, CEC 2011 and CEC 2014 competitions. The algorithm combines a multi-population adaptive Differential Evolution with local search and local and global restart procedures. The proposed algorithm implements a simple but effective mechanism to avoid multiple detections of the same local minima. The novel mechanism allows the algorithm to decide whether to start or not a local search. The local restart of the population, which follows the local search, is, therefore, automatically adapted.
ORCID iDs
Di Carlo, Marilena ORCID: https://orcid.org/0000-0001-5046-3028, Vasile, Massimiliano ORCID: https://orcid.org/0000-0001-8302-6465 and Minisci, Edmondo ORCID: https://orcid.org/0000-0001-9951-8528;-
-
Item type: Book Section ID code: 53402 Dates: DateEvent10 September 2015Published25 February 2015AcceptedSubjects: Technology > Mechanical engineering and machinery
Technology > Motor vehicles. Aeronautics. AstronauticsDepartment: Faculty of Engineering > Mechanical and Aerospace Engineering
Technology and Innovation Centre > Advanced Engineering and ManufacturingDepositing user: Pure Administrator Date deposited: 16 Jun 2015 15:58 Last modified: 20 Dec 2024 01:04 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/53402