Globally Convergent Methods for <i>n</i> -Dimensional Multiextremal Optimization
OptimizationPublished 1 January 1986
János D. Pintér
Citations55
SJR quartileQ2
SJR score0.70
SNIP1.37
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Abstract
A general class of n-dimensional direct (derivative-free) optimization procedures is introduced for solving multiextremal mathematical programming problems. For the case of minimizing a Lipschitz-continuous objective function on an n-dimensional interval, sufficient global convergence conditions are formulated and an efficiency estimate is given. Finally, some numerical aspects of the presented theoretical framework are summarized.
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Computer ScienceMathematics
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