SFDE: Shuffled Frog-Leaping Differential Evolution and Its Application on Cognitive Radio Throughput
Autor: | Hongbo Wang, Xuyan Tu, Xiaoxiao Zhen |
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Rok vydání: | 2019 |
Předmět: |
Mathematical optimization
education.field_of_study Optimization problem Article Subject lcsh:T Computer Networks and Communications Computer science Population lcsh:Technology lcsh:Telecommunication Cognitive radio Robustness (computer science) lcsh:TK5101-6720 Differential evolution Benchmark (computing) Electrical and Electronic Engineering education Throughput (business) Information Systems |
Zdroj: | Wireless Communications and Mobile Computing, Vol 2019 (2019) |
ISSN: | 1530-8677 1530-8669 |
DOI: | 10.1155/2019/2965061 |
Popis: | Differential Evolution (abbreviation for DE) is showing many advantages in solving optimization problems, such as fast convergence, strong robustness, and so on. However, when DE faces a complex target space, the diversity of its population will degenerate in a small scope; even sometimes it is premature to fall into the local minimum. All things contend in beauty in the world; a Shuffled Frog Leaping Algorithm (abbreviation for SFLA) has a strong global ability; unfortunately, its convergence speed is also slow. In order to overcome the shortcoming, this article suggests a Shuffled Frog-leaping Differential Evolution (abbreviation for SFDE) algorithm in a cognitive radio network, which combines Differential Evolution with Shuffled Frog Leaping Algorithm. This proposed method hikes its local searching for a certain number of subgroups, and their individuals join together and share their mutual information among different subgroups, which improves the population diversity and achieves the purpose of fast global search during the whole Differential Evolution. The SFDE is examined by 20 well-known numerical benchmark functions, and those obtained results are compared with four other related algorithms. The experimental simulation in solving the problem of effective throughput optimization for cognitive users shows that the proposed SFDE is effective. |
Databáze: | OpenAIRE |
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