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Effect of Population Size Over Parameter-less Firefly Algorithm

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Applications of Firefly Algorithm and its Variants

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

Abstract

Nature-inspired optimization algorithms have proved their efficacy for solving highly nonlinear problems in science and engineering. Firefly Algorithm (FA), which is one of them, has been taken to be broadly discussed here. However, practical studies demonstrate that the proper setting of the FA’s parameters is the key difficulty. FA associates with some sensitive parameters, and proper setting of their values is extremely time-consuming. Therefore, parameter less variants of FA have been proposed in this study by incorporating the adaptive formulation of the control parameters which are free from the tuning procedure. Population size greatly influences the convergence of any nature-inspired optimization algorithm. Generally, lower population size enhances convergence speed but may trap into local optima. While larger population size maintains the diversity but slows down the convergence rate. Therefore, the crucial effect of different population size over FA’s efficiency has also been investigated here. The population size (of considered FA is varied within the size [10, 1280] where it gets doubled in each run starting with \(n = 10\). Therefore, eight instances of FA have been executed, and the best one is considered by the user over different classes of functions. Experimental results also show that the proposed parameter-less FA with a population size between 40 and 80 provides best results by considering optimization ability and consistency over any classes of functions.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Application, Midnapore College (Autonomous), Paschim Medinipur, West Bengal, India

    Krishna Gopal Dhal

  2. Department of Computer Science, Vidyasagar University, Paschim Medinipur, West Bengal, India

    Samarendu Sahoo

  3. Department of Information Technology, Kalyani Government Engineering College, Kalyani, West Bengal, India

    Arunita Das

  4. Department of Engineering & Technological Studies, University of Kalyani, Kalyani, West Bengal, India

    Sanjoy Das

Authors
  1. Krishna Gopal Dhal
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  2. Samarendu Sahoo
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  3. Arunita Das
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  4. Sanjoy Das
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Corresponding author

Correspondence to Krishna Gopal Dhal .

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Editors and Affiliations

  1. Department of Information Technology, Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

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Dhal, K.G., Sahoo, S., Das, A., Das, S. (2020). Effect of Population Size Over Parameter-less Firefly Algorithm. In: Dey, N. (eds) Applications of Firefly Algorithm and its Variants. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-15-0306-1_11

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