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An Improved Quantum Inspired Immune Clone Optimization Algorithm

  • Annavarapu Chandra Sekhara Rao
  • Suresh DaraEmail author
  • Haider Banka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9873)

Abstract

An improved quantum inspired immune clone optimization algorithm is proposed for optimization problem. It is proposed based on the immune clone algorithm and quantum computing theory. The algorithm adopts the quantum bit to express the chromosomes, and uses the quantum gate updating to implement evolutionary of population which can take advantage of the parallelism of quantum computing and the learning, memory capability of the immune system. Quantum observing entropy is introduced to evaluate the population evolutionary level, and relevant parameters are adjusted according to the entropy value. The proposed algorithm is tested on few benchmark optimization functions and the results are compared with other existing algorithms. The simulation results show that the proposed algorithm has better convergence, robustness and precision.

Keywords

Differential Evolution Artificial Immune System Quantum Gate Firefly Algorithm Immune Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Annavarapu Chandra Sekhara Rao
    • 1
  • Suresh Dara
    • 1
    Email author
  • Haider Banka
    • 1
  1. 1.Department of Computer Science and EngineeringIndian School of MinesDhanbadIndia

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