Real-Observation Quantum-Inspired Evolutionary Algorithm for a Class of Numerical Optimization Problems

  • Gexiang Zhang
  • Haina Rong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4490)

Abstract

This paper proposes a real-observation quantum-inspired evolutionary algorithm (RQEA) to solve a class of globally numerical optimization problems with continuous variables. By introducing a real observation and an evolutionary strategy, suitable for real optimization problems, based on the concept of Q-bit phase, RQEA uses a Q-gate to drive the individuals toward better solutions and eventually toward a single state corresponding to a real number varying between 0 and 1. Experimental results show that RQEA is able to find optimal or close-to-optimal solutions, and is more powerful than conventional real-coded genetic algorithm in terms of fitness, convergence and robustness.

Keywords

Evolutionary computation quantum-inspired evolutionary algorithm real observation numerical optimization 
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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Gexiang Zhang
    • 1
  • Haina Rong
    • 1
  1. 1.School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031 SichuanChina

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