Feedback Functions in Problems of Nonlinear Programming

Volume 7, Issue 5, October 2022     |     PP. 67-82      |     PDF (357 K)    |     Pub. Date: September 12, 2022
DOI: 10.54647/mathematics11348    110 Downloads     5551 Views  

Author(s)

A.E. Umnov, Russian Federation, 141700 Dolgoprudny, MO, Institutskiy per., 9, Moscow Institute of Physics and Technology(National Research University)
E.A. Umnov, Russian Federation, 141700 Dolgoprudny, MO, Institutskiy per., 9, Moscow Institute of Physics and Technology(National Research University)

Abstract
The article considers a method for solving a nonlinear programming problem. This method uses special feedback functions that describe the relationship between direct variables and Lagrange multipliers. These relations are similar to the conditions of the Karush-Kuhn-Tucker theorem, but do not use inequalities in their notation. With the help of feedback functions, a modified Lagrange function is constructed, the saddle points of which can be used as approximate solution of a nonlinear programming problem. The rationale for this scheme is given and an example of its use is demonstrated.

Keywords
nonlinear programming problem. Feedback functions. Modified Lagrange function. Saddle trajectory. Sequential extrapolation method.

Cite this paper
A.E. Umnov, E.A. Umnov, Feedback Functions in Problems of Nonlinear Programming , SCIREA Journal of Mathematics. Volume 7, Issue 5, October 2022 | PP. 67-82. 10.54647/mathematics11348

References

[ 1 ] A.E. Umnov and E.A. Umnov. Using Feedback Functions in Linear Programming Problems, // Computational Mathematics and Mathematical Physics, 2019, Vol. 59, No. 10, pp. 1626–1638. Pleiades Publishing, Ltd., 2019.
[ 2 ] Dimitri P. Bertsekas. Nonlinear Programming. Athena Scientific, Belmont MA, 2016.
[ 3 ] Fiacco~А.V., McCormic~G.P. Nonlinear Programming. Sequential Unconstrained Minimization Techniques. N.Y.~: John Wiley and Sons, 1968.
[ 4 ] Umnov А.Е. Multi-step linear extrapolation in the penalty function method // Computational Mathematics and Mathematical Physics. 1974. V.~14, №~6. - pp.~1451-1463. (in Russian).
[ 5 ] Bazaraa M.S., Sherali H.D., Shetty C.M. Nonlinear programming: Theory and Algorithms. New Jersey, John Wiley \& Sons, Inc., 2006.
[ 6 ] Sukharev А.G., Timochov А.V., Fedorov V.V. Course of optimization methods. Мjscow.~: Fizmatlit, 2011. (in Russian).
[ 7 ] Jorge Nocedal, Stephen J. Wright. Numerical Optimization. Springer-Verlag, Berlin, New-York, 2006.
[ 8 ] Germeyer Ju.B. Introduction to Operations Research Theory. Мoscow.~:Nauka, 1971. (in Russian).
[ 9 ] Skarin V.D. Approximation and regularizing properties of penalty functions and Lagrange functions in mathematical programming. Abstract of the dissertation for the degree of Ph.D., IMM UB RAS. Yekaterinburg, 2010. (in Russian).
[ 10 ] Faddeev D.K. Algebra Lectures. Мoscow.~:Nauka, 1984. (in Russian).
[ 11 ] Steven G. Krantz, Harold R. Parks. The Implicit Function Theorem: History, Theory and Application. Birkhauser, Boston, Basel, Berlin, 2013.
[ 12 ] Kudryavtsev L.D. A Course in Mathematical Analysis. V.~2. Мoscow.~: Vyshaja Shkola, 1981. (in Russian).