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Modified Piyavskii’s Global One-Dimensional Optimization of a Differentiable Function
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作者 Rachid Ellaia Mohamed Zeriab Es-Sadek hasnaa kasbioui 《Applied Mathematics》 2012年第10期1306-1320,共15页
Piyavskii’s algorithm maximizes a univariate function satisfying a Lipschitz condition. We propose a modified Piyavskii’s sequential algorithm which maximizes a univariate differentiable function f by iteratively co... Piyavskii’s algorithm maximizes a univariate function satisfying a Lipschitz condition. We propose a modified Piyavskii’s sequential algorithm which maximizes a univariate differentiable function f by iteratively constructing an upper bounding piece-wise concave function Φ of f and evaluating f at a point where Φ reaches its maximum. We compare the numbers of iterations needed by the modified Piyavskii’s algorithm (nC) to obtain a bounding piece-wise concave function Φ whose maximum is within ε of the globally optimal value foptwith that required by the reference sequential algorithm (nref). The main result is that nC≤ 2nref + 1 and this bound is sharp. We also show that the number of iterations needed by modified Piyavskii’s algorithm to obtain a globally ε-optimal value together with a corresponding point (nB) satisfies nBnref + 1 Lower and upper bounds for nref are obtained as functions of f(x) , ε, M1 and M0 where M0 is a constant defined by M0 = supx∈[a,b] - f’’(x) and M1 ≥ M0 is an evaluation of M0. 展开更多
关键词 GLOBAL OPTIMIZATION Piyavskii’s ALGORITHM
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