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Neural Computing and Applications

, Volume 29, Issue 2, pp 435–445 | Cite as

Synthesis of linear antenna array using flower pollination algorithm

  • Urvinder Singh
  • Rohit Salgotra
Original Article

Abstract

Linear antenna array (LAA) design is a classical electromagnetic problem. It has been extensively dealt by number of researchers in the past, and different optimization algorithms have been applied for the synthesis of LAA. This paper presents a relatively new optimization technique, namely flower pollination algorithm (FPA) for the design of LAA for reducing the maximum side lobe level (SLL) and null control. The desired antenna is achieved by controlling only amplitudes or positions of the array elements. FPA is a novel meta-heuristic optimization method based on the process of pollination of flowers. The effectiveness and capability of FPA have been proved by taking difficult instances of antenna array design with single and multiple objectives. It is found that FPA is able to provide SLL reduction and steering the nulls in the undesired interference directions. Numerical results of FPA are also compared with the available results in the literature of state-of-the-art algorithms like genetic algorithm, particle swarm optimization, cuckoo search, tabu search, biogeography based optimization (BBO) and others which also proves the better performance of the proposed method. Moreover, FPA is more consistent in giving optimum results as compared to BBO method reported recently in the literature.

Keywords

Antenna Linear antenna array Optimization Flower pollination algorithm Evolutionary computing 

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Copyright information

© The Natural Computing Applications Forum 2016

Authors and Affiliations

  1. 1.Thapar UniversityPatialaIndia
  2. 2.Chandigarh UniversityMohaliIndia

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