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Global convergence of a class of trust region algorithms for optimization with simple bounds. (English) Zbl 0643.65031
This paper extends the known global convergence properties of trust region algorithms for un-constrained optimization to the case where bounds on the variables are presented in the form f(x)$$=^{!}Min$$, $$\ell_ i\leq x_ i\leq u_ i$$, $$(i=1,...,n)$$. These extensions are obtained by generalizing the classical notion of Cauchy point and by considering generaion see Zbl 0641.00024.]
For the problem: $$\epsilon y''+p(x)y'=f(x)$$, $$-\alpha y(0)+y'(0)=\alpha_ 0$$, $$y(1)=\alpha_ 1$$, p(x)$$\geq \bar p>0$$, the cubic spline collocation method is derived. Uniform convergence of first order on locally bounded mesh is achieved. The method has second order convergence for fixed $$\epsilon$$.

MSC:
 65K05 Numerical mathematical programming methods 90C30 Nonlinear programming
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