F-MOGP: A Novel Many-Objective Evolutionary Approach to QoS-Aware Data Intensive Web Service Composition
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- @InProceedings{Yu:2015:CEC,
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author = "Yang Yu and Hui Ma and Mengjie Zhang",
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title = "{F-MOGP}: A Novel Many-Objective Evolutionary Approach
to {QoS}-Aware Data Intensive Web Service Composition",
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booktitle = "Proceedings of 2015 IEEE Congress on Evolutionary
Computation (CEC 2015)",
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year = "2015",
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editor = "Yadahiko Murata",
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pages = "2843--2850",
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address = "Sendai, Japan",
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month = "25-28 " # may,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-4799-7491-7",
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DOI = "doi:10.1109/CEC.2015.7257242",
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abstract = "QoS-aware web service composition has attracted
increasing attention recently. Meanwhile, due to the
explosion in the volume of data, providing efficient
methods for composing data intensive services poses new
challenges to the service composition problem. In this
paper, a new search and optimisation approach based on
a reduced space searching strategy, named F-MOGP, is
presented to address the problem of QoS-aware data
intensive service composition driven by four
conflicting quality objectives. The experimental
results show that the proposed approach is
computationally efficient by search space reduction.
Compared with the existing single-objective and
multi-objective optimization methods, a set of
higher-quality data intensive service compositions can
be successfully generated to support decision makers by
providing them with potential trade-offs among
different objectives.",
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notes = "1030 hrs 15578 CEC2015",
- }
Genetic Programming entries for
Yang Yu
Hui Ma
Mengjie Zhang
Citations