Evolutionary Web Service Composition: A Graph-based Memetic Algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Yan:2016:CEC,
  author =       "Longfei Yan and Yi Mei and Hui Ma and Mengjie Zhang",
  title =        "Evolutionary Web Service Composition: A Graph-based
                 Memetic Algorithm",
  booktitle =    "Proceedings of 2016 IEEE Congress on Evolutionary
                 Computation (CEC 2016)",
  year =         "2016",
  editor =       "Yew-Soon Ong",
  pages =        "201--208",
  address =      "Vancouver",
  month =        "24-29 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-5090-0623-6",
  DOI =          "doi:10.1109/CEC.2016.7743796",
  abstract =     "Web Service Composition (WSC) is a prominent way of
                 actualizing service-oriented architecture by
                 integrating network-accessible Web services into a new
                 invokable application. Evolutionary computation
                 techniques have provided rewarding approaches in
                 automatic Web service composition over the last decade.
                 However, the studies on considering both functionality
                 and non-functionality (i.e. Quality-of-Service, QoS)
                 properties are still limited. In this paper, we propose
                 a novel Graph-Based Memetic Algorithm (GBMA) for
                 solving the QoS-aware WSC problems. GBMA adopts the
                 graph representation proposed by GraphEvol, which is
                 one of the state-of-the-art algorithms. More
                 importantly, GBMA designs and uses a local search based
                 on two newly designed move operators to overcome the
                 drawbacks of the mutation operator in GraphEvol. The
                 experimental results show that the proposed GBMA
                 outperformed GraphEvol, which is the counterpart
                 without local search, in terms of both solution quality
                 and convergence speed. This demonstrates the efficacy
                 and efficiency of combining local search with global
                 search in solving QoS-aware WSC problems.",
  notes =        "WCCI2016",
}

Genetic Programming entries for Longfei Yan Yi Mei Hui Ma Mengjie Zhang

Citations