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Performance Analysis of Hybrid Memory Based Dragonfly Algorithm in Engineering Problems

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Advances in Swarm Intelligence

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1054))

Abstract

Hybrid Memory Based Dragonfly Algorithm with Differential Evolution (DADE) is one of the most prominent swarm-based optimization techniques due to its better computational complexity and high convergence rate for achieving optimum results. In DADE, the best solution is memorized and processed with Differential Evolution (DE) for enhanced diversity and balanced exploration and exploitation rate. DADE brings two distinct advantages: First, the superior convergence rate due to continuous update of personal best individual in the search process. Second, better exploration due to the inclusion of global best and global worst individuals in the hybridization process. Comparative simulations have been performed on 24 standard benchmark functions along with the benchmark function of CEC2005 and CEC2017. Comparative analysis of the result demonstrates the competitiveness of the DADE algorithm in terms of optimal cost, computational complexity and convergence characteristics compared to other considered optimization algorithms.

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Author information

Authors and Affiliations

  1. Department of ECE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India

    Sanjoy Debnath

  2. Department of ECE, National Institute of Technology Silchar, Assam, India

    Ravi Singh Kurmvanshi & Wasim Arif

Authors
  1. Sanjoy Debnath
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  2. Ravi Singh Kurmvanshi
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  3. Wasim Arif
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Corresponding author

Correspondence to Sanjoy Debnath .

Editor information

Editors and Affiliations

  1. Department of CS and Engineering, National Institute Of Technology Silchar, Cachar, Assam, India

    Anupam Biswas

  2. Department of Industrial Engineering, Pamukkale Ãœniversitesi Hastaneleri, Pamukkale, Turkey

    Can B. Kalayci

  3. Centre for AI Research and Optimisation, Torrens University Australia, Brisbane, QLD, Australia

    Seyedali Mirjalili

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Debnath, S., Kurmvanshi, R.S., Arif, W. (2023). Performance Analysis of Hybrid Memory Based Dragonfly Algorithm in Engineering Problems. In: Biswas, A., Kalayci, C.B., Mirjalili, S. (eds) Advances in Swarm Intelligence. Studies in Computational Intelligence, vol 1054. Springer, Cham. https://doi.org/10.1007/978-3-031-09835-2_5

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