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Efficient multi-objective services selection algorithm based on particle swarm optimization
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2010 (English)In: Proceedings - 2010 IEEE Asia-Pacific Services Computing Conference, APSCC 2010, IEEE , 2010, 603-608 p.Conference paper (Refereed)
Abstract [en]

With the development of Web Service, it has become a key issue to select appropriate services from a large number of candidates for creating complex composite services according to users' different QoS levels requirements. However, the existing service selection algorithms have many defects such as high time complexity, non-global optimal solutions, and poor quality solutions. To solve these defects, an efficient multi-objective services selection algorithm, EMOSS, is proposed in this paper based on particle swarm optimization. The essence of EMOSS is to model the service selection problem as a constrained multi-objective optimization problem. First the services in each sub-service set are sorted by their concept of domination, then the new sub-service set nSi , whose size is far less than the original one, is constructed and finally output pareto optimal set. The theoretical analysis and experimental results show that EMOSS can effectively obtain high quality solutions.

Place, publisher, year, edition, pages
IEEE , 2010. 603-608 p.
Keyword [en]
Multi-objective particle swarm optimization algorithm, Service composition, Service selection
National Category
Other Computer and Information Science
URN: urn:nbn:se:kth:diva-150040DOI: 10.1109/APSCC.2010.75ScopusID: 2-s2.0-79952372830ISBN: 978-076954305-5OAI: diva2:742397
2010 IEEE Asia-Pacific Services Computing Conference, APSCC 2010, 6 December 2010 through 10 December 2010, Hangzhou, China

QC 20140901

Available from: 2014-09-01 Created: 2014-08-29 Last updated: 2014-09-01Bibliographically approved

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Mao, Bo
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Geoinformatics (closed 20110301)
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