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00000cam a2200000 i 4500 |
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on1310341759 |
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OCoLC |
| 005 |
20240909213021.0 |
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m o d |
| 007 |
cr un|---aucuu |
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220409s2021 sz ob 001 0 eng d |
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|a EBLCP
|b eng
|c EBLCP
|d YDX
|d GW5XE
|d OCLCO
|d OCLCF
|d VLB
|d OCLCQ
|d S9M
|d OCLCL
|d OCLCQ
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| 019 |
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|a 1306528038
|a 1308393277
|a 1308795240
|a 1309032021
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| 020 |
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|a 9783030762759
|q (electronic bk.)
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| 020 |
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|a 3030762750
|q (electronic bk.)
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| 020 |
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|z 9783030762742
|q (hbk.)
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| 020 |
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|z 3030762742
|q (hbk.)
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| 024 |
7 |
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|a 10.1007/978-3-030-76275-9
|2 doi
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| 035 |
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|a (OCoLC)1310341759
|z (OCoLC)1306528038
|z (OCoLC)1308393277
|z (OCoLC)1308795240
|z (OCoLC)1309032021
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| 050 |
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4 |
|a QA402.5
|b .R69 2021eb
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| 072 |
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7 |
|a MAT003000
|2 bisacsh
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| 049 |
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|a HCDD
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| 100 |
1 |
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|a Royset, Johannes O.,
|e author.
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| 245 |
1 |
3 |
|a An optimization primer /
|c Johannes O. Royset, Roger J.-B. Wets.
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| 264 |
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|a Cham :
|b Springer,
|c 2021.
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| 264 |
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4 |
|c ©2021
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| 300 |
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|a 1 online resource (xviii, 676 pages : illustrations)
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
1 |
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|a Springer series in operations research and financial engineering
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| 500 |
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|a Description based upon print version of record.
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| 505 |
0 |
0 |
|t PRELUDE --
|t CONVEX OPTIMIZATION --
|t OPTIMIZATION UNDER UNCERTAINTY --
|t MINIMIZATION PROBLEMS --
|t PERTURBATION AND DUALITY --
|t WITHOUT CONVEXITY OR SMOOTHNESS --
|t GENERALIZED EQUATIONS --
|t RISK MODELING AND SAMPLE AVERAGES --
|t GAMES AND MINSUP PROBLEMS --
|t DECOMPOSITION.
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| 504 |
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|a Includes bibliographical references and index.
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| 520 |
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|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.
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| 650 |
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0 |
|a Mathematical optimization.
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| 650 |
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7 |
|a Optimización matemática
|2 embne
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| 650 |
|
7 |
|a Mathematical optimization
|2 fast
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| 700 |
1 |
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|a Wets, Roger J.-B.,
|e author.
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| 758 |
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|i has work:
|a OPTIMIZATION PRIMER (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCXKRf689jcKHFyvtQrPWjC
|4 https://id.oclc.org/worldcat/ontology/hasWork
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| 776 |
0 |
8 |
|i Print version:
|a Royset, Johannes O.,
|t Optimization primer
|z 9783030762742
|w (OCoLC)1295112977
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| 830 |
|
0 |
|a Springer series in operations research.
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| 856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-76275-9
|y Click for online access
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| 903 |
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|a SPRING-MATH2021
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| 994 |
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|a 92
|b HCD
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