Towards Many-objective Optimisation with Hyper-heuristics: Identifying Good Heuristics with Indicators
dc.contributor.author | Walker, David | |
dc.contributor.author | Keedwell, EC | |
dc.date.accessioned | 2018-09-28T13:55:14Z | |
dc.date.available | 2018-09-28T13:55:14Z | |
dc.date.issued | 2016-09-17 | |
dc.identifier.isbn | 9783319458229 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.issn | 1611-3349 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/12430 | |
dc.description.abstract |
The use of hyper-heuristics is increasing in the multiobjective optimisation domain, and the next logical advance in such methods is to use them in the solution of many-objective problems. Such problems comprise four or more objectives and are known to present a significant challenge to standard dominance-based evolutionary algorithms. We incorporate three comparison operators as alternatives to dominance and investigate their potential to optimise many-objective problems with a hyper-heuristic from the literature. We discover that the best results are obtained using either the favour relation or hypervolume, but conclude that changing the comparison operator alone will not allow for the generation of estimated Pareto fronts that are both close to and fully cover the true Pareto front. | |
dc.format.extent | 493-502 | |
dc.language.iso | en | |
dc.publisher | Springer International Publishing | |
dc.title | Towards Many-objective Optimisation with Hyper-heuristics: Identifying Good Heuristics with Indicators | |
dc.type | conference | |
dc.type | Conference Proceeding | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000387962100046&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.volume | 9921 | |
plymouth.conference-name | Parallel Problem Solving from Nature (PPSN2016) | |
plymouth.publication-status | Published | |
plymouth.journal | PARALLEL PROBLEM SOLVING FROM NATURE - PPSN XIV | |
dc.identifier.doi | 10.1007/978-3-319-45823-6_46 | |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering | |
plymouth.organisational-group | /Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dcterms.dateAccepted | 2016-05-30 | |
dc.identifier.eissn | 1611-3349 | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.1007/978-3-319-45823-6_46 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2016-09-17 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract |