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Quantum-Inspired Evolutionary Algorithm for Continuous Space Optimization Based on Multiple Chains Encoding Method of Quantum Bits

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  • Rui Zhang
  • Zhiteng Wang
  • Hongjun Zhang

Abstract

This study proposes a novel quantum evolutionary algorithm called four-chain quantum-inspired evolutionary algorithm (FCQIEA) based on the four gene chains encoding method. In FCQIEA, a chromosome comprises four gene chains to expand the search space effectively and promote the evolutionary rate. Different parameters, including rotational angle and mutation probability, have been analyzed for better optimization. Performance comparison with other quantum-inspired evolutionary algorithms (QIEAs), evolutionary algorithms, and different chains of QIEA demonstrates the effectiveness and efficiency of FCQIEA.

Suggested Citation

  • Rui Zhang & Zhiteng Wang & Hongjun Zhang, 2014. "Quantum-Inspired Evolutionary Algorithm for Continuous Space Optimization Based on Multiple Chains Encoding Method of Quantum Bits," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-16, July.
    • Handle: RePEc:hin:jnlmpe:620325
    DOI: 10.1155/2014/620325
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    Cited by:

    1. Tiberiu Stefan Letia & Elenita Maria Durla-Pasca & Dahlia Al-Janabi & Octavian Petru Cuibus, 2022. "Development of Evolutionary Systems Based on Quantum Petri Nets," Mathematics, MDPI, vol. 10(23), pages 1-34, November.

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