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Cuckoo Search and Firefly Algorithm pp 217–243Cite as

Hybridization of Cuckoo Search and Firefly Algorithms for Selecting the Optimal Solution in Semantic Web Service Composition

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 516))

Abstract

This chapter investigates how the Cuckoo Search and Firefly Algorithm can be hybridized for performance improvement in the context of selecting the optimal or near-optimal solution in semantic Web service composition. Cuckoo Search and Firefly Algorithm are hybridized with genetic, reinforcement learning and tabu principles to achieve a proper exploration and exploitation of the search process. The hybrid algorithms are applied on an enhanced planning graph which models the service composition search space for a given user request. The problem of finding the optimal solution encoded in the enhanced planning graph can be reduced to identifying a configuration of semantic Web services, out of a very large set of possible configurations, which maximizes a fitness function which considers semantics and QoS attributes as selection criteria. To analyze the benefits of hybridization we have comparatively evaluated the classical Cuckoo Search and Firefly Algorithms versus the proposed hybridized algorithms.

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Authors and Affiliations

  1. Computer Science Department, Technical University of Cluj-Napoca, 26-28 G. Baritiu street, Cluj-Napoca, Romania

    Ioan Salomie, Viorica Rozina Chifu & Cristina Bianca Pop

Authors
  1. Ioan Salomie
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  2. Viorica Rozina Chifu
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  3. Cristina Bianca Pop
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Corresponding authors

Correspondence to Ioan Salomie , Viorica Rozina Chifu or Cristina Bianca Pop .

Editor information

Editors and Affiliations

  1. School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

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Salomie, I., Chifu, V.R., Pop, C.B. (2014). Hybridization of Cuckoo Search and Firefly Algorithms for Selecting the Optimal Solution in Semantic Web Service Composition. In: Yang, XS. (eds) Cuckoo Search and Firefly Algorithm. Studies in Computational Intelligence, vol 516. Springer, Cham. https://doi.org/10.1007/978-3-319-02141-6_11

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  • DOI: https://doi.org/10.1007/978-3-319-02141-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02140-9

  • Online ISBN: 978-3-319-02141-6

  • eBook Packages: EngineeringEngineering (R0)

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