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  • Many-Objective Optimization of Antenna Arrays Using an Improved Multiple-Single-Objective Pareto Sampling Algorithm

    Author(s)
    Liu, L
    Lu, J
    Yang, S
    Griffith University Author(s)
    Lu, Junwei
    Year published
    2012
    Metadata
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    Abstract
    Pareto-based multiobjective evolutionary algorithms are recognized as the standards for solving multiobjective antenna design problems. However, when the number of objectives exceeds three, these algorithms always exhibit deficiencies in searching the Pareto front. To eliminate these deficiencies, several algorithms, such as Hyper-volume Estimation (HypE) algorithm and Multiple- Single-Objective Pareto Sampling (MSOPS) algorithm, are introduced. In this letter, an improved MSOPS algorithm is proposed. The numerical results on many-objective optimal designs of a linear antenna array and a Yagi-Uda array have demonstrated that ...
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    Pareto-based multiobjective evolutionary algorithms are recognized as the standards for solving multiobjective antenna design problems. However, when the number of objectives exceeds three, these algorithms always exhibit deficiencies in searching the Pareto front. To eliminate these deficiencies, several algorithms, such as Hyper-volume Estimation (HypE) algorithm and Multiple- Single-Objective Pareto Sampling (MSOPS) algorithm, are introduced. In this letter, an improved MSOPS algorithm is proposed. The numerical results on many-objective optimal designs of a linear antenna array and a Yagi-Uda array have demonstrated that the proposed algorithm outperforms its ancestor, NSGA II, and HypE as well.
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    Journal Title
    IEEE Antennas and Wireless Propagation Letters
    Volume
    11
    DOI
    https://doi.org/10.1109/LAWP.2012.2193653
    Subject
    Communications engineering
    Publication URI
    http://hdl.handle.net/10072/49545
    Collection
    • Journal articles

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