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Performance Comparison of Pattern Search, Simulated Annealing, Genetic Algorithm and Jaya Algorithm

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Data Engineering and Intelligent Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 542 ))

Abstract

In this paper, we have shown the performance comparison of four powerful global optimization algorithms, namely Pattern Search, Simulated Annealing, Genetic Algorithm and Jaya Algorithm. All of these algorithms are used to find an optimum solution. The standard benchmark functions are utilized for the implementation. The results are collected and analyzed that helps to classify the algorithms according to their computational capability to solve the optimization problems.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Amity University, Sector-125, Noida, Uttar Pradesh , India

    Hari Mohan Pandey, Manjul Rajput & Varun Mishra

Authors
  1. Hari Mohan Pandey
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  2. Manjul Rajput
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  3. Varun Mishra
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Corresponding author

Correspondence to Hari Mohan Pandey .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, India

    Suresh Chandra Satapathy

  2. Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Department of Computer Science and Engineering, CMR Technical Campus, Hyderabad, India

    K. Srujan Raju

  4. DVR and Dr. HS MIC College of Technology, Kanchikacherla, Andhra Pradesh, India

    B. Janakiramaiah

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Pandey, H.M., Rajput, M., Mishra, V. (2018). Performance Comparison of Pattern Search, Simulated Annealing, Genetic Algorithm and Jaya Algorithm. In: Satapathy, S., Bhateja, V., Raju, K., Janakiramaiah, B. (eds) Data Engineering and Intelligent Computing. Advances in Intelligent Systems and Computing, vol 542 . Springer, Singapore. https://doi.org/10.1007/978-981-10-3223-3_36

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  • DOI: https://doi.org/10.1007/978-981-10-3223-3_36

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3222-6

  • Online ISBN: 978-981-10-3223-3

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