Diversity Measures in Artificial Bee Colony

  • Harish Sharma
  • Jagdish Chand Bansal
  • K. V. Arya
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 201)

Abstract

Artificial Bee Colony (ABC) is a recent swarm intelligence based approach to solve nonlinear and complex optimization problems. Exploration and exploitation are the two important characteristics of the swarm based optimization algorithms. Exploration capability of an algorithm is the capability of exploring the solution space to find the possible solution while exploitation capability of an algorithm is the capability of exploiting a particular region of the search space for a better solution. Usually, exploration and exploitation capabilities are contradictory in nature, i.e., a better exploration capability results a worse exploitation capability and vice versa. An economic and efficient algorithm can explore the complete solution space and shows a convergent behavior after a finite number of trials. Exploration and exploitation capabilities, are quantified using various diversity measures. In this paper, an analytical study has been carried out for various diversity measures for ABC process.

Keywords

Diversity measures Swarm intelligence Exploration-Exploitation Artificial bee colony 

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Copyright information

© Springer India 2013

Authors and Affiliations

  • Harish Sharma
    • 1
  • Jagdish Chand Bansal
    • 2
  • K. V. Arya
    • 1
  1. 1.ABV-Indian Institute of Information Technology and ManagementGwaliorIndia
  2. 2.South Asian UniversityNew DelhiIndia

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