Document Zbl 0628.90074

from until

One-Line Search

add line

Document Type:

Journal Articles

Collection Articles

Books

arXiv Preprints

Document Type:

Journal Articles

Collection Articles

Books

arXiv Preprints

Reset all

New Multi-Line Search

Help

Examples

Geometry Search for the term Geometry in any field. Queries are case-independent.

Funct* Wildcard queries are specified by * (e.g. functions, functorial, etc.). Otherwise the search is exact.

"Topological group" Phrases (multi-words) should be set in "straight quotation marks".

au: Bourbaki & ti: Algebra Search for author and title. The and-operator & is default and can be omitted.

Chebyshev | Tschebyscheff The or-operator | allows to search for Chebyshev or Tschebyscheff.

Quasi* map* py: 1989 The resulting documents have publication year 1989.

so: Eur* J* Mat* Soc* cc: 14 Search for publications in a particular source with a Mathematics Subject Classification code (cc) in 14.

"Partial diff* eq*" ! elliptic The not-operator ! eliminates all results containing the word elliptic.

dt: b & au: Hilbert The document type is set to books; alternatively: j for journal articles, a for book articles.

py: 2000-2015 cc: (94A | 11T) Number ranges are accepted. Terms can be grouped within (parentheses).

la: chinese Find documents in a given language. ISO 639-1 language codes can also be used.

Fields

any	anywhere
an	internal document identifier
au	author, editor
ai	internal author identifier
ti	title
la	language
so	source
ab	review, abstract
py	publication year
rv	reviewer
cc	MSC code
ut	uncontrolled term
dt	document type (j: journal article; b: book; a: book article)

Operators

a & b	logic and
a \| b	logic or
!ab	logic not
abc*	right wildcard
"ab c"	phrase
(ab c)	parentheses

The minimum risk approach to max-min bilinear programming. (English) Zbl 0628.90074

An. Științ. Univ. Al. I. Cuza Iași, N. Ser., Secț. Ia 31, 205-209 (1985).

The max-min bilinear programming problem is investigated and the minimum risk approach for it is formulated. The authors reduce this problem under certain hypotheses to a max-min bilinear fractional problem which is deterministic and does not depend on the distribution function of the random variables. A parametrical algorithm for solving the max-min bilinear fractional problem is proposed. The convergence of the proposed algorithm as well as the finiteness of an approximate variant is based on the theorem stated in the paper.

Reviewer: R.G.Vachnadze

MSC:

90C31	Sensitivity, stability, parametric optimization
65K05	Numerical mathematical programming methods

Keywords:

max-min bilinear programming; minimum risk approach; parametrical algorithm

Cite Review PDF