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Taguchi-Based Tuning of Rotation Angles and Population Size in Quantum-Inspired Evolutionary Algorithm for Solving MMDP

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Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 236))

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Abstract

Quantum-inspired evolutionary algorithms (QEAs) have been successfully used for solving search and optimization problems. QEAs employ quantum rotation gates as variation operator. The selection of rotation angles in the quantum gate has been mostly performed intuitively. This paper presents tuning of the parameters by designing experiments using well-known Taguchi’s method with massively multimodal deceptive problem as the benchmark.

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Authors and Affiliations

  1. Department of Mathematics, Dayalbagh Educational Institute, Dayalbagh, Agra, India

    Nija Mani,  Gursaran & A. K. Sinha

  2. USIC, Dayalbagh Educational Institute, Dayalbagh, Agra, India

    Ashish Mani

Authors
  1. Nija Mani
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  2. Gursaran
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  3. A. K. Sinha
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  4. Ashish Mani
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Corresponding author

Correspondence to Nija Mani .

Editor information

Editors and Affiliations

  1. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    B. V. Babu

  2. Department of Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

  3. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  4. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

  5. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  6. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Kanad Ray

  7. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Umesh Gupta

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Mani, N., Gursaran, Sinha, A.K., Mani, A. (2014). Taguchi-Based Tuning of Rotation Angles and Population Size in Quantum-Inspired Evolutionary Algorithm for Solving MMDP. In: Babu, B., et al. Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012. Advances in Intelligent Systems and Computing, vol 236. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_12

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  • DOI: https://doi.org/10.1007/978-81-322-1602-5_12

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1601-8

  • Online ISBN: 978-81-322-1602-5

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