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A novel bat flower pollination algorithm for synthesis of linear antenna arrays

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Abstract

In this paper, a novel algorithm, namely bat flower pollination (BFP) is proposed for synthesis of unequally spaced linear antenna array (LAA). The new method is a combination of bat algorithm (BA) and flower pollination algorithm (FPA). In BFP, both BA and FPA interact with each other to escape from local minima. The results of BFP for solving a set of 13 benchmark functions demonstrate its superior performance as compared to variety of well-known algorithms available in the literature. The novel proposed method is also used for the synthesis of unequally spaced LAA for single and multi-objective design. Simulation results show that BFP is able to provide better synthesis results than wide range of popular techniques like genetic algorithm, differential evolution, cuckoo search, particle swarm optimization, back scattering algorithm and others.

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Correspondence to Rohit Salgotra.

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Salgotra, R., Singh, U. A novel bat flower pollination algorithm for synthesis of linear antenna arrays. Neural Comput & Applic 30, 2269–2282 (2018). https://doi.org/10.1007/s00521-016-2833-3

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