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Optimization of Antenna Lattice Towers using Genetic Algorithm
This paper presents the design optimization of antenna lattice towers using genetic algorithm (GA). Design optimization of the antenna tower includes arriving at optimum configuration with respect to the bracing system and cross-sectional parameters of members when the weight of the tower is minimum satisfying a set of specified constraints. The variables considered for design optimization of tower are type of bracing in each panel and the cross-sectional properties of members. The proposed GA is mathematically formulated as a constrained nonlinear optimization problem. The components of the GA are described. The traditional GA is modified to handle this problem. Simple concepts such as selection of mutation probability and member grouping are used to accelerate convergence and reduce the computational effort. Numerical examples are given to validate developed algorithm and the examples with different bracing configurations.
Optimization of Antenna Lattice Towers using Genetic Algorithm
This paper presents the design optimization of antenna lattice towers using genetic algorithm (GA). Design optimization of the antenna tower includes arriving at optimum configuration with respect to the bracing system and cross-sectional parameters of members when the weight of the tower is minimum satisfying a set of specified constraints. The variables considered for design optimization of tower are type of bracing in each panel and the cross-sectional properties of members. The proposed GA is mathematically formulated as a constrained nonlinear optimization problem. The components of the GA are described. The traditional GA is modified to handle this problem. Simple concepts such as selection of mutation probability and member grouping are used to accelerate convergence and reduce the computational effort. Numerical examples are given to validate developed algorithm and the examples with different bracing configurations.
Optimization of Antenna Lattice Towers using Genetic Algorithm
J. Inst. Eng. India Ser. A
Arjun, V. (Autor:in) / Anjan, B. K. (Autor:in) / Kanmani, S. S. (Autor:in) / Umesha, P. K. (Autor:in)
Journal of The Institution of Engineers (India): Series A ; 103 ; 557-565
01.06.2022
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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