SNO multi-objective implementation for sparse array optimization

The aim of this paper is to present the adaptation of an Evolutionary Algorithm, Social Network Optimization (SNO) to multi-objective benchmark function. The algorithm will be presented in his basic implementation and then the modifications will be shown. Then it will be used to find the Pareto fron...

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Bibliographic Details
Published in:2017 International Conference on Electromagnetics in Advanced Applications (ICEAA) pp. 824 - 827
Main Authors: Grimaccia, Francesco, Mussetta, Marco, Niccolai, Alessandro, Pirinoli, Paola, Zich, Riccardo E.
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2017
Subjects:
Antenna radiation patterns
Correlation
Indexes
Linear programming
Pareto optimization
Social network services
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Summary:The aim of this paper is to present the adaptation of an Evolutionary Algorithm, Social Network Optimization (SNO) to multi-objective benchmark function. The algorithm will be presented in his basic implementation and then the modifications will be shown. Then it will be used to find the Pareto front of a sparse array.
DOI:10.1109/ICEAA.2017.8065378