Geometric particle swarm optimization in Program Trace Optimization
dc.contributor.author | Moraglio, A | |
dc.contributor.author | McDermott, J | |
dc.date.accessioned | 2025-03-12T16:11:00Z | |
dc.date.issued | 2025 | |
dc.date.updated | 2025-03-12T15:41:28Z | |
dc.description.abstract | On the 30th anniversary of Particle Swarm Optimization (PSO), we present a novel integration of Geometric PSO (GPSO) into the Program Trace Optimization (PTO) framework. GPSO extends PSO to diverse representations in a principled manner, while PTO provides automatic representation design for arbitrary problem structures. By specializing GPSO to PTO’s trace representation, we achieve a universal PSO variant applicable out-of-the-box to any representation and problem. We detail the theoretical foundations of this integration and evaluate our approach on diverse optimization problems across multiple representations. Our work demonstrates the power of combining geometric generalizations with automatic representation design, here specifically obtaining a truly general form of PSO that applies to any representation while retaining its original essence. | en_GB |
dc.identifier.citation | Applications of Evolutionary Computation - 28th European Conference, EvoApplications 2025, held as Part of EvoStar 2025, 23-25 April 2025, Trieste, Italy. Awaiting full citation and DOI | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/140606 | |
dc.language.iso | en | en_GB |
dc.publisher | Springer Nature | en_GB |
dc.relation.url | https://link.springer.com/book/9783031900648 | |
dc.rights.embargoreason | Under temporary indefinite embargo pending publication by Springer Nature. No embargo required on publication | en_GB |
dc.rights | © 2025 The author(s). For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. | en_GB |
dc.title | Geometric particle swarm optimization in Program Trace Optimization | en_GB |
dc.type | Conference paper | en_GB |
dc.date.available | 2025-03-12T16:11:00Z | |
dc.contributor.editor | Hart, E | |
dc.identifier.issn | 0302-9743 | |
exeter.location | Trieste | |
dc.description | This is the author accepted manuscript. | en_GB |
dc.identifier.eissn | 1611-3349 | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2025-01-10 | |
dcterms.dateSubmitted | 2024-11-15 | |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2025-01-10 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract | en_GB |
refterms.dateFCD | 2025-03-12T15:41:30Z | |
refterms.versionFCD | AM | |
refterms.panel | B | en_GB |
pubs.name-of-conference | EvoApplications | |
exeter.rights-retention-statement | No |
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Except where otherwise noted, this item's licence is described as © 2025 The author(s). For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.