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Evaluation of random gradient techniques for unconstrained optimization

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Abstract

The random gradient method is first evaluated analytically in connection with «Adaptive Step Size Random Search» (A.S.S.R.S.). The random weighted gradient technique (R. W. G) is proposed as an effective algorithm for unconstrained optimization. Its implementation and numerical performance on some test problems are analyzed.

Riassunto

Il metodo del gradiente statistico viene dapprima valutato analiticamente confrontandolo con «Adaptive Step Size Random Search» (A.S.S.R.S.). La tecnica del gradiente statistico pesato (R.W.G.) viene proposta come un algoritmo efficace per la ottimizzazione non vincolata. Si esaminano successivamente la realizzazione dell'algoritmo ed il suo comportamento numerico per alcuni problemi test.

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Authors and Affiliations

  1. Laboratorio di Analisi Numerica, Ricercatore C.N.R., Pavia

    F. Archetti

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  1. F. Archetti
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Archetti, F. Evaluation of random gradient techniques for unconstrained optimization. Calcolo 12, 83–94 (1975). https://doi.org/10.1007/BF02576717

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  • DOI: https://doi.org/10.1007/BF02576717

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