國立虎尾科技大學 |

An Optimization Primer

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	An Optimization Primer/ by Johannes O. Royset, Roger J-B Wets.
作者:	Royset, Johannes O.
其他作者:	Wets, Roger J-B.
面頁冊數:	XVIII, 676 p. 155 illus., 55 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Optimization. -
電子資源:	https://doi.org/10.1007/978-3-030-76275-9
ISBN:	9783030762759

An Optimization Primer
Royset, Johannes O.

An Optimization Primer[electronic resource] /by Johannes O. Royset, Roger J-B Wets. - 1st ed. 2021. - XVIII, 676 p. 155 illus., 55 illus. in color.online resource. - Springer Series in Operations Research and Financial Engineering,2197-1773. - Springer Series in Operations Research and Financial Engineering,.

Prelude -- Convex optimization -- Optimization under uncertainty -- Minimization problems -- Perturbation and duality -- Without convexity or smoothness -- Generalized Equations -- Risk modeling and sample averages -- Games and minsup problems -- Decomposition.

This richly illustrated book introduces the subject of optimization to a broad audience with a balanced treatment of theory, models and algorithms. Through numerous examples from statistical learning, operations research, engineering, finance and economics, the text explains how to formulate and justify models while accounting for real-world considerations such as data uncertainty. It goes beyond the classical topics of linear, nonlinear and convex programming and deals with nonconvex and nonsmooth problems as well as games, generalized equations and stochastic optimization. The book teaches theoretical aspects in the context of concrete problems, which makes it an accessible onramp to variational analysis, integral functions and approximation theory. More than 100 exercises and 200 fully developed examples illustrate the application of the concepts. Readers should have some foundation in differential calculus and linear algebra. Exposure to real analysis would be helpful but is not prerequisite. .

ISBN: 9783030762759

Standard No.: 10.1007/978-3-030-76275-9doiSubjects--Topical Terms:

669174
Optimization.

LC Class. No.: QA402.5-402.6

Dewey Class. No.: 519.6

An Optimization Primer
LDR:02724nam a22004095i 4500 001 1059466
003 DE-He213
005 20220328103343.0
007 cr nn 008mamaa
008 220414s2021 sz | s |||| 0|eng d
020 $a 9783030762759 $9 978-3-030-76275-9
024 7 $a 10.1007/978-3-030-76275-9 $2 doi
035 $a 978-3-030-76275-9
050 4 $a QA402.5-402.6
072 7 $a PBU $2 bicssc
072 7 $a MAT003000 $2 bisacsh
072 7 $a PBU $2 thema
082 0 4 $a 519.6 $2 23
100 1 $a Royset, Johannes O. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1107471
245 1 3 $a An Optimization Primer $h [electronic resource] / $c by Johannes O. Royset, Roger J-B Wets.
250 $a 1st ed. 2021.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a XVIII, 676 p. 155 illus., 55 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Springer Series in Operations Research and Financial Engineering, $x 2197-1773
505 0 $a Prelude -- Convex optimization -- Optimization under uncertainty -- Minimization problems -- Perturbation and duality -- Without convexity or smoothness -- Generalized Equations -- Risk modeling and sample averages -- Games and minsup problems -- Decomposition.
520 $a This richly illustrated book introduces the subject of optimization to a broad audience with a balanced treatment of theory, models and algorithms. Through numerous examples from statistical learning, operations research, engineering, finance and economics, the text explains how to formulate and justify models while accounting for real-world considerations such as data uncertainty. It goes beyond the classical topics of linear, nonlinear and convex programming and deals with nonconvex and nonsmooth problems as well as games, generalized equations and stochastic optimization. The book teaches theoretical aspects in the context of concrete problems, which makes it an accessible onramp to variational analysis, integral functions and approximation theory. More than 100 exercises and 200 fully developed examples illustrate the application of the concepts. Readers should have some foundation in differential calculus and linear algebra. Exposure to real analysis would be helpful but is not prerequisite. .
650 1 4 $a Optimization. $3 669174
650 0 $a Mathematical optimization. $3 527675
700 1 $a Wets, Roger J-B. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1366172
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030762742
776 0 8 $i Printed edition: $z 9783030762766
776 0 8 $i Printed edition: $z 9783030762773
830 0 $a Springer Series in Operations Research and Financial Engineering, $x 1431-8598 $3 1267183
856 4 0 $u https://doi.org/10.1007/978-3-030-76275-9
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)