Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/113404
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DC Field | Value | Language |
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dc.contributor.author | Shi, F. | - |
dc.contributor.author | Schirneck, M. | - |
dc.contributor.author | Friedrich, T. | - |
dc.contributor.author | Kötzing, T. | - |
dc.contributor.author | Neumann, F. | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Algorithmica: an international journal in computer science, 2019; 81(2):1-30 | - |
dc.identifier.issn | 0178-4617 | - |
dc.identifier.issn | 1432-0541 | - |
dc.identifier.uri | http://hdl.handle.net/2440/113404 | - |
dc.description.abstract | Rigorous runtime analysis is a major approach towards understanding evolutionary computing techniques, and in this area linear pseudo-Boolean objective functions play a central role. Having an additional linear constraint is then equivalent to the NP-hard Knapsack problem, certain classes thereof have been studied in recent works. In this article, we present a dynamic model of optimizing linear functions under uniform constraints. Starting from an optimal solution with respect to a given constraint bound, we investigate the runtimes that different evolutionary algorithms need to recompute an optimal solution when the constraint bound changes by a certain amount. The classical (1+1) EA and several population-based algorithms are designed for that purpose, and are shown to recompute efficiently. Furthermore, a variant of the (1+(λ,λ)) GA for the dynamic optimization problem is studied, whose performance is better when the change of the constraint bound is small. | - |
dc.description.statementofresponsibility | Feng Shi, Martin Schirneck, Tobias Friedrich, Timo Kötzing, Frank Neumann | - |
dc.language.iso | en | - |
dc.publisher | Springer | - |
dc.rights | © Springer Science+Business Media, LLC, part of Springer Nature 2018 | - |
dc.source.uri | http://dx.doi.org/10.1007/s00453-018-0451-4 | - |
dc.subject | Evolutionary algorithm | - |
dc.subject | Runtime analysis | - |
dc.subject | Reoptimization time | - |
dc.subject | Dynamic constraint | - |
dc.subject | Uniform constraint | - |
dc.title | Reoptimization Time Analysis of Evolutionary Algorithms on Linear Functions Under Dynamic Uniform Constraints | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1007/s00453-018-0451-4 | - |
dc.relation.grant | http://purl.org/au-research/grants/arc/DP140103400 | - |
dc.relation.grant | http://purl.org/au-research/grants/arc/DP160102401 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Neumann, F. [0000-0002-2721-3618] | - |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
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