The design of genetic operators is absolutely one of the core work of evolutionary algorithms research. However, the essence of the evolutionary algorithms is that a lot of algorithm design is based on the manual resu...
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The design of genetic operators is absolutely one of the core work of evolutionary algorithms research. However, the essence of the evolutionary algorithms is that a lot of algorithm design is based on the manual result analysis, summarize, refine, feedback, and then, the algorithms are designed adaptively and correspondingly. This kind of design scheme needs artificial statistics and analysis of large amounts of data, which greatly increases the burden of the designers. To solve this problem, an evolutionary algorithm framework based on genetic operator automatic design is proposed in this paper. In the first step, Gene Expression Programming and differentialevolution methods are combined together and used to design the genetic operators automatically and adaptively, this hybrid method can not only explore solutions in problem space for the problem solving as most classical evolutionary algorithms do, but also generate genetic operators automatically in operator space for the proper operators extraction and selection related to the evolutionary algorithms . In the second step, the designed operators are adopted into the typical evolutionary algorithms to verify the performance and the result shows that the new designed genetic operator is superior to or at least equivalent to some existing DE variants in a set of classical benchmark functions. More importantly, this paper is not aimed at designing high performance algorithms, but to provide a new perspective for algorithms designing, and to provide a reference scheme for the machine algorithms designing.
A wideband circularly polarised array antenna consisting of 10-element bowtie dipole antenna and feed network is presented. A narrow patch connecting the pair of bowtie dipoles as an entity is employed to achieve high...
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A wideband circularly polarised array antenna consisting of 10-element bowtie dipole antenna and feed network is presented. A narrow patch connecting the pair of bowtie dipoles as an entity is employed to achieve high gain. To obtain wideband and flat-top beam of radiation patterns, amplitude and phase distribution along the feed are optimised by application of the self-adaptivedifferentialevolutionalgorithm. Particularly, the feed network with broadband phase shift performance is designed to satisfy bandwidth requirement ranging from 1.1 to 1.6 GHz. The proposed antenna can achieve an excellent impedance matching and Axial Ratio characteristics over the entire operating band. Moreover, the ripple of co-polarisation radiation pattern covering +/- 12 degrees in the elevation plane is better than 0.92 dB;whereas the gain is also better than 11.8 dB and the side lobes are below -13 dB. Measured results validate the design concept and indicate that the proposed array exhibits good radiation characteristics.
Memetic algorithms are population-based meta-heuristic search algorithms that combine the composite benefits of natural and cultural evolution. In this paper a synergism of the classical differentialevolution algorit...
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ISBN:
(纸本)9781467315098
Memetic algorithms are population-based meta-heuristic search algorithms that combine the composite benefits of natural and cultural evolution. In this paper a synergism of the classical differentialevolutionalgorithm and Q-learning is used to construct the memetic algorithm. Computer simulation with standard benchmark functions reveals that the proposed memetic algorithm outperforms three distinct differentialevolutionalgorithms.
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