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dc.contributor.authorMostaghim, Sanaz
dc.contributor.authorPfeiffer, Friederike
dc.contributor.authorSchmeck, Hartmut
dc.date.accessioned2017-12-06T09:06:16Z
dc.date.available2017-12-06T09:06:16Z
dc.date.issued2011
dc.identifier.issn0177-0454
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/8557
dc.description.abstractThe parallelization of optimization algorithms is very beneficial when the function evaluations of optimization problems are time consuming. However, parallelization gets very complicated when we deal with a large number of parallel resources. In this paper, we present a framework called Self-organized Invasive Parallel Optimization (SIPO) in which the resources are self-organized. The optimization starts with a small number of resources which decide the number of further required resources on-demand. This means that more resources are stepwise added or eventually released from the platform. In this paper, we study an undesired effect in such a self-organized system and propose a self-repairing mechanism called Recovering-SIPO. These frameworks are tested on a series of multi-objective optimization problems.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofPARS: Parallel-Algorithmen, -Rechnerstrukturen und -Systemsoftware: Vol. 28, No. 1
dc.relation.ispartofseriesPARS: Parallel-Algorithmen, -Rechnerstrukturen und -Systemsoftware
dc.subjectShared Memory
dc.subjectMultiobjective Optimization
dc.subjectSelection Mechanism
dc.subjectParallel Optimization
dc.subjectParallel Platform
dc.titleSelf-organized Invasive Parallel Optimization with Self-repairing Mechanismen
dc.typeText/Journal Article
mci.reference.pages90-99
dc.identifier.doi10.1007/BF03341988


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