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Social Group Optimization Algorithm for Pattern Optimization in Antenna Arrays

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Socio-cultural Inspired Metaheuristics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 828))

Abstract

Over a decade, the evolutionary and social inspired computing techniques have revolutionarised the nonlinear problem-solving methods with their efficiency in searching for the global optimum solutions. Several engineering problems are dealt with such nature-inspired techniques. In the recent past, the evolutionary computing and socio-inspired algorithms have been applied to antenna array synthesis problems. In this chapter, the novel social group optimization algorithm (SGOA) is used for the antenna array synthesis. Three different and potential pattern synthesis problems like sidelobe level (SLL) optimization, null positioning, and failure compensation are dealt for demonstrating the effectiveness of the SGOA over the conventional uniform patterns. In all the cases, the simulation-based experimentation is repeated for 20-element and 28-element linear array. The robustness of the algorithm to deal with the constrained objectives of antenna array synthesis is discussed with relevant outcomes from the simulations in terms of the convergence plots.

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Author information

Authors and Affiliations

  1. Department of Electronics & Communication Engineering, Raghu Institute of Technology, Visakhapatnam, India

    V. V. S. S. S. Chakravarthy & P. S. R. Chowdary

  2. School of Computer Engineering, KIIT (Deemed to be University), Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  3. Department of Electronics and Telecommunications, Universitat Ramon Llull, Barcelona, Spain

    Jaume Anguera

  4. Technology Department, Fractus Antennas, Barcelona, Spain

    Jaume Anguera & Aurora Andújar

Authors
  1. V. V. S. S. S. Chakravarthy
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  2. P. S. R. Chowdary
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  3. Suresh Chandra Satapathy
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  4. Jaume Anguera
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  5. Aurora Andújar
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Corresponding author

Correspondence to V. V. S. S. S. Chakravarthy .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, Maharashtra, India

    Anand J. Kulkarni

  2. ABV-Indian Institute of Information Technology and Management Gwalior, Gwalior, Madhya Pradesh, India

    Pramod Kumar Singh

  3. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Deemed to be University, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  4. Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

    Ali Husseinzadeh Kashan

  5. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore

    Kang Tai

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Chakravarthy, V.V.S.S.S., Chowdary, P.S.R., Satapathy, S.C., Anguera, J., Andújar, A. (2019). Social Group Optimization Algorithm for Pattern Optimization in Antenna Arrays. In: Kulkarni, A.J., Singh, P.K., Satapathy, S.C., Husseinzadeh Kashan, A., Tai, K. (eds) Socio-cultural Inspired Metaheuristics. Studies in Computational Intelligence, vol 828. Springer, Singapore. https://doi.org/10.1007/978-981-13-6569-0_13

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