LEADER 05912nam 22007815 450 001 9910254929403321 005 20220308130128.0 010 $a3-319-18842-9 024 7 $a10.1007/978-3-319-18842-3 035 $a(CKB)3710000000436757 035 $a(SSID)ssj0001558265 035 $a(PQKBManifestationID)16182826 035 $a(PQKBTitleCode)TC0001558265 035 $a(PQKBWorkID)14818973 035 $a(PQKB)11042735 035 $a(DE-He213)978-3-319-18842-3 035 $a(MiAaPQ)EBC6314199 035 $a(MiAaPQ)EBC5591972 035 $a(Au-PeEL)EBL5591972 035 $a(OCoLC)912293299 035 $a(PPN)186399987 035 $a(EXLCZ)993710000000436757 100 $a20150625d2016 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aLinear and Nonlinear Programming$b[electronic resource] /$fby David G. Luenberger, Yinyu Ye 205 $a4th ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (XIII, 546 p. 90 illus.) 225 1 $aInternational Series in Operations Research & Management Science,$x0884-8289 ;$v228 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-319-18841-0 327 $aIntroduction -- Part I Linear Programming -- Basic Properties of Linear Programs -- The Simplex Method -- Duality and Complementarity -- Interior-Point Methods -- Conic Linear Programming -- Part II Unconstrained Problems -- Basic Properties of Solutions and Algorithms -- Basic Descent Methods -- Conjugate Direction Methods -- Quasi-Newton Methods -- Part III Constrained Minimization -- Constrained Minimization Conditions -- Primal Methods -- Penalty and Barrier Methods -- Duality and Dual Methods -- Primal-Dual Methods -- Appendix A: Mathematical Review -- Appendix B: Convex Sets -- Appendix C: Gaussian Elimination -- Appendix D: Basic Network Concepts. 330 $aThis new edition covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. Again a connection between the purely analytical character of an optimization problem and the behavior of algorithms used to solve the problem. As in the earlier editions, the material in this fourth edition is organized into three separate parts. Part I is a self-contained introduction to linear programming covering numerical algorithms and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. Part III extends the concepts developed in the second part to constrained optimization problems. It is possible to go directly into Parts II and III omitting Part I, and, in fact, the book has been used in this way in many universities.