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Local and global optimization by parallel algorithms for MIMD systems

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Abstract

This paper describes an implementation on the Neptune system at Loughborough University of Sutti's parallel (MIMD) algorithm [1–3] and an analysis of its performance. Parallel asynchronous versions of Powell's method [6] and Price's algorithm [7] are proposed, designed for efficient implementation on MIMD systems.

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References

  1. C. Sutti, Nongradient minimization methods for parallel processing computers, part 1, J.O.T.A. 19, No. 4(1983)

  2. C. Sutti, Nongradient minimization methods for parallel processing computers, part 2, J.O.T.A. 19, No. 4(1983).

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  10. J.J. McKeown, Aspects of parallel computation in numerical optimization, Tech. Rep. 108, N.O.C. Hatfield Polytechnic, Herts, U.K., 1980.

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Authors and Affiliations

  1. Mathematical Department, University of Lecce, Italy, Michele in Bosco, I-46010 S, Mantova, Italy

    C. Sutti

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  1. C. Sutti
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Additional information

This work has been developed during the author's stay at the Numerical Optimization Centre, Hatfield Polytechnic, England.

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Sutti, C. Local and global optimization by parallel algorithms for MIMD systems. Ann Oper Res 1, 151–164 (1984). https://doi.org/10.1007/BF01876145

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  • DOI: https://doi.org/10.1007/BF01876145

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