Efficient stochastic local search algorithm for solving the shortest common supersequence problem
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00171014" target="_blank" >RIV/68407700:21230/10:00171014 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Efficient stochastic local search algorithm for solving the shortest common supersequence problem
Original language description
Recently, an application of the iterative optimization method called Prototype Optimization with Evolved Improvement Steps (POEMS) to the SCS problem has been proposed. This paper proposes a new time efficient evaluation procedure and a new moving-windowstrategy for constructing and refining the supersequence. These two enhancements significantly improve an efficiency of the approach. Series of experiments with the modified POEMS method have been carried out. Results presented in this paper show that the method is competitive with current state-of-the-art algorithms for solving the SCS problem.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 12th annual conference comp on Genetic and evolutionary computation
ISBN
978-1-4503-0073-5
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
ACM
Place of publication
New York
Event location
Portland, Oregon
Event date
Jul 7, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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