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Diskretn. Anal. Issled. Oper., 2018, Volume 25, Issue 2, Pages 82–100 (Mi da897)  

Complexity estimation for an algorithm of searching for zero of a piecewise linear convex function

E. V. Prosolupov, G. Sh. Tamasyan

St. Petersburg State University, 35 Universitetskii Ave., 198504 St. Petersburg, Russia

Abstract: It is known that the problem of the orthogonal projection of a point to the standard simplex can be reduced to solution of a scalar equation. In this article, the complexity is analyzed of an algorithm of searching for zero of a piecewise linear convex function which is proposed by N. Maculan and G. Galdino de Paula, Jr. (Oper. Res. Lett. 8 (4), 219–222 (1989)). The analysis is carried out of the best and worst cases of the input data for the algorithm. To this end, the largest and smallest numbers of iterations of the algorithm are studied as functions of the size of the input data. It is shown that, in the case of equality of elements of the input set, the algorithm performs the smallest number of iterations. In the case of different elements of the input set, the number of iterations is maximal and depends rather weakly on the particular values of the elements of the set. The results of numerical experiments with random input data of large dimension are presented. Tab. 2, illustr. 2, bibliogr. 34.

Keywords: standard simplex, orthogonal projection of a point, zeros of function.

DOI: https://doi.org/10.17377/daio.2018.25.571

Full text: PDF file (408 kB)
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English version:
Journal of Applied and Industrial Mathematics, 2018, 12:2, 325–333

UDC: 519.8
Received: 10.03.2017
Revised: 26.12.2017

Citation: E. V. Prosolupov, G. Sh. Tamasyan, “Complexity estimation for an algorithm of searching for zero of a piecewise linear convex function”, Diskretn. Anal. Issled. Oper., 25:2 (2018), 82–100; J. Appl. Industr. Math., 12:2 (2018), 325–333

Citation in format AMSBIB
\Bibitem{ProTam18}
\by E.~V.~Prosolupov, G.~Sh.~Tamasyan
\paper Complexity estimation for an algorithm of searching for zero of a~piecewise linear convex function
\jour Diskretn. Anal. Issled. Oper.
\yr 2018
\vol 25
\issue 2
\pages 82--100
\mathnet{http://mi.mathnet.ru/da897}
\crossref{https://doi.org/10.17377/daio.2018.25.571}
\elib{https://elibrary.ru/item.asp?id=34875797}
\transl
\jour J. Appl. Industr. Math.
\yr 2018
\vol 12
\issue 2
\pages 325--333
\crossref{https://doi.org/10.1134/S1990478918020126}
\scopus{https://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85047840847}


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