Strawberry algorithm and its newly evolved variant for pattern nulling in an antenna array
RAIRO. Operations Research, Tome 55 (2021), pp. S1089-S1111

In this article attempt has been made for the first time to apply the reported strawberry optimization technique to antenna array synthesis problem. The algorithm is further modified by reinforcing it with adaptive values for the two key parameters known as runner length and root length embedded in the mathematical expression governing the movement of the mother plant from one position to another in the search space to locate the optimum solution. The case studies cited here refer to linear and circular array configurations. The design constraints are limited to minimizing the side lobe level and restricting the first null beam width, which play significant roles in antenna array performances. The important features which greatly influence in achieving the said objectives are either placement of antenna elements or amplitudes of excitations of these elements or both. And the recently reported nature inspired metaheuristic optimization algorithms have addressed to these antenna problems quite effectively and the application of the strawberry algorithm for the first time and the unraveling of a new algorithm known as reduced step size strawberry algorithm (rss-SBA) a variant of the existing SBA have shown quite exciting results thus opening avenues for these techniques to be the potential contenders in the race of authenticating their positions in the domain of nonlinear function optimization.

Reçu le :
Accepté le :
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DOI : 10.1051/ro/2020048
Classification : 00.XX
Keywords: Strawberry algorithm, metaheuristic algorithms, antenna array, optimization, nature inspired techniques
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     title = {Strawberry algorithm and its newly evolved variant for pattern nulling in an antenna array},
     journal = {RAIRO. Operations Research},
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     doi = {10.1051/ro/2020048},
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Konidala, Subhashini R. Strawberry algorithm and its newly evolved variant for pattern nulling in an antenna array. RAIRO. Operations Research, Tome 55 (2021), pp. S1089-S1111. doi: 10.1051/ro/2020048

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