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Dual-Population Co-Evolution Multi-Objective Optimization Algorithm and Its Application: Power Allocation Optimization of Mobile Base Stations

Dual-Population Co-Evolution Multi-Objective Optimization Algorithm and Its Application: Power Allocation Optimization of Mobile Base Stations

Yu Bo, Fahui Gu
Copyright: © 2022 |Volume: 16 |Issue: 1 |Pages: 21
ISSN: 1557-3958|EISSN: 1557-3966|EISBN13: 9781683180197|DOI: 10.4018/IJCINI.296258
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MLA

Bo, Yu, and Fahui Gu. "Dual-Population Co-Evolution Multi-Objective Optimization Algorithm and Its Application: Power Allocation Optimization of Mobile Base Stations." IJCINI vol.16, no.1 2022: pp.1-21. http://doi.org/10.4018/IJCINI.296258

APA

Bo, Y. & Gu, F. (2022). Dual-Population Co-Evolution Multi-Objective Optimization Algorithm and Its Application: Power Allocation Optimization of Mobile Base Stations. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 16(1), 1-21. http://doi.org/10.4018/IJCINI.296258

Chicago

Bo, Yu, and Fahui Gu. "Dual-Population Co-Evolution Multi-Objective Optimization Algorithm and Its Application: Power Allocation Optimization of Mobile Base Stations," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 16, no.1: 1-21. http://doi.org/10.4018/IJCINI.296258

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Abstract

In the multi-objective optimization algorithm, the parameter strategy has a huge impact on the performance of the algorithm, and it is difficult to set a set of parameters with excellent distribution and convergence performance in the actual optimization process. Based on the MOEA/D algorithm framework, this paper construct an improved dual-population co-evolution MOEA/D algorithm by adopt the idea of dual-population co-evolution. The simulation test of the benchmark functions shows that the proposed dual-population co-evolution MOEA/D algorithm have significant improvements in IGD and HV indicators compare with three other comparison algorithms. Finally, the application of the LTE base station power allocation model also verifies the effectiveness of the proposed algorithm.