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dc.contributor.authorYuzhen, Geen_US
dc.contributor.authorWatson, Layne T.en_US
dc.date.accessioned2013-06-19T14:36:22Z
dc.date.available2013-06-19T14:36:22Z
dc.date.issued1999-09-01
dc.identifierhttp://eprints.cs.vt.edu/archive/00000507/en_US
dc.identifier.urihttp://hdl.handle.net/10919/20009
dc.description.abstractOptimization problems represent a class of problems that can be time consuming to solve and very complex. In this paper, a quantum algorithm for solving optimization problems is proposed. The algorithm utilizes the encoding scheme from genetic algorithms to encode the problem and then uses Grover's unitary transformation to seek out a solution. The efficiency of the algorithm depends on the length of the chromosome or the coded variable. As a simple example the satisfiability problem, an NP-complete problem, is examined using the algorithm and the time complexity of solving this problem is greatly improved. The traveling salesman and minimum spanning tree problems are also briefly discussed.en_US
dc.format.mimetypeapplication/postscripten_US
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen_US
dc.relation.ispartofHistorical Collection(Till Dec 2001)en_US
dc.titleQuantum Computing Applied to Optimizationen_US
dc.typeTechnical reporten_US
dc.identifier.trnumberTR-99-03en_US
dc.type.dcmitypeTexten_US
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00000507/01/TR-99-03.ps


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