03443nam a22003975i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001800153072001600171072002300187072001500210100014300225245008800368250001800456264008200474300004200556336002600598337002600624338003600650347002400686490004900710505007600759520193400835650003102769650001802800710003402818773002602852776003602878776003602914830004902950856004602999978-3-662-69741-2DE-He21320251030113049.0cr nn 008mamaa240917s2024    gw |    s    |||| 0|eng d  a97836626974127 a10.1007/978-3-662-69741-22doi 4aQA402.5-402.6 7aPBU2bicssc 7aMAT0420002bisacsh 7aPBU2thema1 aStein, Oliver.eauthor.0(orcid)0000-0001-9514-63171https://orcid.org/0000-0001-9514-63174aut4http://id.loc.gov/vocabulary/relators/aut10aBasic Concepts of Nonlinear Optimizationh[electronic resource] /cby Oliver Stein.  a1st ed. 2024. 1aBerlin, Heidelberg :bSpringer Berlin Heidelberg :bImprint: Springer,c2024.  aX, 214 p. 43 illus.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aMathematics Study Resources,x2731-3832 ;v80 aIntroduction -- Unconstrained Optimization -- Constrained Optimization.  aThis textbook is an introduction to nonlinear optimization, which treats mathematical concepts stringently on the one hand, but also motivates them in great detail and illustrates them with 42 figures. Therefore, the book is not only aimed at mathematicians, but also at natural scientists, engineers, and economists who want to understand and apply mathematically sound methods in their field. With just over two hundred pages, the book offers sufficient flexibility to serve as a foundation for various types of lectures on nonlinear optimization. Many geometric approaches for understanding both optimality conditions and numerical methods introduce a new perspective, enriching the existing literature on optimization. This is particularly evident in the detailed treatment of issues arising from different functional descriptions of the same geometry of feasible sets, and the thus motivated introduction of constraint qualifications for deriving derivative-based optimality conditions. The author Prof. Dr. Oliver Stein is a full professor at the Karlsruhe Institute of Technology, where he heads the Continuous Optimization group at the Institute for Operations Research. His research focuses on the design and implementation of optimization methods and their theoretical foundations. His teaching focuses on global optimization, nonlinear optimization, mixed-integer optimization, convex analysis, parametric optimization, and multiobjective optimization. This book is the English translation of the second edition of “Grundzüge der Nichtlinearen Optimierung” (Springer, 2021) written in German. The translation was done with the help of artificial intelligence. A subsequent revision was performed by the author to further refine the work and to ensure that the translation is appropriate concerning content and scientific correctness. It may, however, read stylistically different from a conventional translation. 0aMathematical optimization.14aOptimization.2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978366269740508iPrinted edition:z9783662697429 0aMathematics Study Resources,x2731-3832 ;v840uhttps://doi.org/10.1007/978-3-662-69741-2