JACIII Vol.15 No.8 pp. 1095-1102
doi: 10.20965/jaciii.2011.p1095


Performance Analysis of Quantum-Inspired Evolutionary Algorithm

Tomohisa Takata, Teijiro Isokawa, and Nobuyuki Matsui

Graduate School of Engineering, University of Hyogo, 2167 Shosha, Himeji, Hyogo 671-2280, Japan

March 5, 2011
July 15, 2011
October 20, 2011
quantum-inspired, evolutionary algorithm, Knapsack problem, maximum search, image filtering
Quantum-Inspired Evolutionary Algorithm (QEA) is an extension of evolutionary algorithm in which quantum mechanics and its representations are introduced. A chromosome in QEA is represented as a series of qubits (quantum bits), and phase-rotation gates are embedded into the selection process over generations. This algorithm has been shown to have better performances than the classical ones in small benchmark problems, but this has not yet been applied to larger scale problems. We show the performances of this QEA by solving the Knapsack problem, maximum search problem, and construction of image filter. We also investigate the diversity of individuals in a population in order to estimate the robustness against environmental changes.
Cite this article as:
T. Takata, T. Isokawa, and N. Matsui, “Performance Analysis of Quantum-Inspired Evolutionary Algorithm,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.8, pp. 1095-1102, 2011.
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