GP-Based Approach to Comprehensive Quality-Aware Automated Semantic Web Service Composition

Created by W.Langdon from gp-bibliography.bib Revision:1.4472

  author =       "Chen Wang and Hui Ma and Aaron Chen and 
                 Sven Hartmann",
  title =        "{GP}-Based Approach to Comprehensive Quality-Aware
                 Automated Semantic Web Service Composition",
  booktitle =    "Proceedings of the 11th International Conference on
                 Simulated Evolution and Learning, SEAL-2017",
  year =         "2017",
  editor =       "Yuhui Shi and Kay Chen Tan and Mengjie Zhang and 
                 Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and 
                 Martin Middendorf and Yaochu Jin",
  volume =       "10593",
  series =       "Lecture Notes in Computer Science",
  pages =        "170--183",
  address =      "Shenzhen, China",
  month =        nov # " 10-13",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-319-68759-9",
  URL =          "",
  DOI =          "doi:10.1007/978-3-319-68759-9_15",
  size =         "14 pages",
  abstract =     "Comprehensive quality-aware semantic web service
                 composition aims to optimise semantic matchmaking
                 quality and Quality of service (QoS) simultaneously. It
                 is an NP-hard problem due to its huge search space.
                 Therefore, heuristics have to be employed to generate
                 near-optimal solutions. Existing works employ
                 Evolutionary Computation (EC) techniques to solve
                 combinatorial optimisation problems in web service
                 composition. In particular, Genetic Programming (GP)
                 has shown its promise. The tree-based representation
                 used in GP is flexible to represent different
                 composition constructs as inner nodes, but the semantic
                 matchmaking information can not be directly obtained
                 from the representation. To overcome this disadvantage,
                 we propose a tree-like representation to directly cope
                 with semantic matchmaking information. Meanwhile, a
                 GP-based approach to comprehensive quality-aware
                 semantic web service composition is proposed with
                 explicit support for our representation. We also design
                 specific genetic operation that effectively maintain
                 the correctness of solutions during the evolutionary
                 process. We conduct experiments to explore the
                 effectiveness and efficiency of our GP-based approach
                 using a benchmark dataset with real-world composition

Genetic Programming entries for Chen Wang Hui Ma Aaron Chen Sven Hartmann