Conformal Array Pattern Synthesis Using a Hybrid GA/ABC Algorithm

DOI

10.2991/aiie-15.2015.70How to use a DOI?

Keywords

conformal array; genetic algorithm (GA); artificial bee colony algorithm (ABC); hybrid GA/ABC algorithm; pattern synthesis

Abstract

A hybrid evolutionary algorithm is presented here to solve the problem of conformal array pattern synthesis. In order to overcome the disadvantage of standard genetic algorithm (GA) and artificial bee colony algorithm (ABC), a hybrid algorithm is introduced, which combines GA and ABC to take advantages of both methods. Crossover operator of GA is adopted to maintain the diversity of population. Multi-dimensional neighborhood search strategy of ABC is introduced to improve the local search efficiency for conformal array pattern synthesis. Finally, the hybrid GA/ABC algorithm is used to optimize the weight vector of the circular conformal array. Experimental results show that the proposed method can achieve the desired pattern very well, and has a better performance than standard GA and ABC.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - C. Liu
AU  - L.H. Fan
PY  - 2015/07
DA  - 2015/07
TI  - Conformal Array Pattern Synthesis Using a Hybrid GA/ABC Algorithm
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 250
EP  - 253
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.70
DO  - 10.2991/aiie-15.2015.70
ID  - Liu2015/07
ER  -