ALGORITHM FOR MINIMIZING A DIFFERENTIABLE FUNCTION SUBJECT TO BOX CONSTRAINTS AND ERRORS

被引:11
作者
BRAYTON, RK
CULLUM, J
机构
[1] Mathematical Sciences Department, IBM, T. J. Watson Research Center, Yorktown Heights, New York
关键词
constrained minimization; nonlinear programming; Quasi-Newton algorithm; symmetric rank-one update;
D O I
10.1007/BF00934451
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We consider the problem of minimizing a differentiable function of n parameters, with upper and lower bounds on the parameters. The motivation for this work comes from the optimization of the design of transient electrical circuits. In such optimization, the parameters are circuit elements, the bound constraints keep these parameters physically meaningful, and both the function and gradient evaluations contain errors. We describe a quasi-Newton algorithm for such problems. This algorithm handles the box constraints directly and approximates the given function locally by nonsingular quadratic functions. Numerical tests indicate that the algorithm can tolerate the errors, if the errors in the function and gradient are of the same relative size. © 1979 Plenum Publishing Corporation.
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页码:521 / 558
页数:38
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