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dc.contributor.authorFieldsend, Jonathan E.
dc.date.accessioned2014-07-22T10:10:42Z
dc.date.issued2014-09-22
dc.description.abstractWe present a new multi-modal evolutionary optimiser, the niching migratory multi-swarm optimiser (NMMSO), which dynamically manages many particle swarms. These sub-swarms are concerned with optimising separate local modes, and employ measures to allow swarm elements to migrate away from their parent swarm if they are identified as being in the vicinity of a separate peak, and to merge swarms together if they are identified as being concerned with the same peak. We employ coarse peak identification to facilitate the mode identification required. Swarm members are not constrained to particular sub- regions of the parameter space, however members are initialised in the vicinity of a swarm’s local mode estimate. NMMSO is shown to cope with a range of problem types, and to produce results competitive with the state-of-the-art on the CEC 2013 multi-modal optimisation competition test problems, providing new benchmark results in the field.en_GB
dc.identifier.citationProceedings of the 2014 IEEE Congress on Evolutionary Computation, Beijing, China, 6 - 11 July 2014, pp. 2593 - 2600en_GB
dc.identifier.doi10.1109/CEC.2014.6900309
dc.identifier.urihttp://hdl.handle.net/10871/15247
dc.language.isoenen_GB
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_GB
dc.relation.urlhttps://github.com/fieldsend/ieee_cec_2014_nmmso
dc.titleRunning Up Those Hills: Multi-Modal Search with the Niching Migratory Multi-Swarm Optimiseren_GB
dc.typeConference paperen_GB
dc.date.available2014-07-22T10:10:42Z
dc.descriptionCopyright © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en_GB
dc.description2014 IEEE Congress on Evolutionary Computation, Beijing, China, 6 - 11 July 2014en_GB
dc.descriptionThe codebase for this paper, containing the NMMSO algorithm, is at https://github.com/fieldsend/ieee_cec_2014_nmmso


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