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

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 framew...

Full description

Saved in:
Bibliographic Details
Published in:International journal of cognitive informatics & natural intelligence 2022-06, Vol.16 (1), p.1-21
Main Authors: Bo, Yu, Gu, Fahui
Format: Article
Language:English
Subjects:
Algorithms
Cellular telephone equipment industry
Mathematical optimization
Wireless telecommunications equipment
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1557-3958
1557-3966
DOI:10.4018/IJCINI.296258