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In this paper, a hybrid approach to service composition is proposed that combines the use of genetic programming and random greedy search. The greedy algorithm is used to generate valid and locally optimized individuals to populate the initial generation for genetic programming (GP), and to perform mutation operations during genetic programming.
A full experimental evaluation has been carried out using public benchmark test cases with repositories of up to 15000 web services and 31000 properties. The results show good performance in searching for best service compositions, where the number of atomic web services used and the tree depth are used as objectives for minimization.
Further, we extend our approach to the more general problem of finding service composition solutions that have near-optimal QoS. Our experimental evaluation demonstrates that our GP-based greedy algorithm enhanced approach can be applied with good performance to the QoS-aware service composition problem.",
The 24th International Conference on Database and Expert Systems Applications (DEXA 2013), with proceedings published as volumes 8055 and 8056 in Springer's Lecture Notes in Computer Science, featured some outstanding keynote presentations and regular articles. As with previous editions of the DEXA conference, the Program Co-chairs of DEXA 2013 invited some of the authors to submit extended papers to a special issue of the Springer journal Transactions on Large-Scale Data- and Knowledge- Centred Systems (TLDKS). Following these invitations, both keynote papers and eight regular articles were submitted. Apart from the keynotes, each submission was carefully assessed by at least two (often more) recognized experts in the respective field. In total, 35 reviews were received, most of them of excellent quality. After two rounds of revisions, five of the eight regular papers were accepted for inclusion in this special issue, in addition to the two keynote papers...
Cites \cite{Aversano:2006:IJCSSE} Aversano:2005:WSEC",
Genetic Programming entries for Hui Ma Anqi Wang Mengjie Zhang