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Combining a Local Search and Grover’s Algorithm in Black-Box Global Optimization

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  • D. W. Bulger

    (Macquarie University)

Abstract

Grover’s quantum algorithm promises a quadratic acceleration for any problem formulable as a search. For unstructured search problems, its implementation and performance are well understood. The curse of dimensionality and the intractability of the general global optimization problem require any identifiable structure or regularity to be incorporated into a solution method. This paper addresses the application of Grover’s algorithm when a local search technique is available, thereby combining the quadratic acceleration with the acceleration seen in the multistart method.

Suggested Citation

  • D. W. Bulger, 2007. "Combining a Local Search and Grover’s Algorithm in Black-Box Global Optimization," Journal of Optimization Theory and Applications, Springer, vol. 133(3), pages 289-301, June.
    • Handle: RePEc:spr:joptap:v:133:y:2007:i:3:d:10.1007_s10957-007-9168-2
    DOI: 10.1007/s10957-007-9168-2
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    References listed on IDEAS

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    1. Samuel H. Brooks, 1958. "A Discussion of Random Methods for Seeking Maxima," Operations Research, INFORMS, vol. 6(2), pages 244-251, April.
    2. D. Bulger & W. P. Baritompa & G. R. Wood, 2003. "Implementing Pure Adaptive Search with Grover's Quantum Algorithm," Journal of Optimization Theory and Applications, Springer, vol. 116(3), pages 517-529, March.
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