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Contents
CONVEX PROGRAMMING | 1 |
Characterizing Optimal Solutions | 13 |
Some Computational Methods | 59 |
Copyright | |
4 other sections not shown
Common terms and phrases
Algorithm 3.9 BEN-ISRAEL BEN-TAL binding constraints characterization Chebyshev solution computational constraint qualification contradicting convex cone convex program convex set denote direction of descent directions of constancy DNLP Dubovitskii-Milyutin equivalent Euler-Lagrange equation Exercises and Examples exists a vector faithfully convex functions feasible direction methods feasible point feasible set feasible solution fk(x Fritz John G Df(x GIRSANOV 72 Hence implies inconsistent index set inequality iteration John condition Kf(x Kuhn-Tucker condition Lemma lexicographic linear program linearly independent MANGASARIAN matrix MELP multipliers necessary condition non-negative nonascent nonempty nonlinear programming optimal solution Pareto minimum Pareto optimality posynomial primal problem Proof pseudoconvex quasiconvex quasiconvex functions quasiusable direction reduction condition relevant intervals satisfying scalars second-order conditions Section separation theorem set of binding Slater's condition subset ft sufficient condition sush thst TH(x Theorem 3.2 tions usable directions zero ZLOBEC
Bibliographic information
| Title | Optimality in nonlinear programming: a feasible directions approach Pure and applied mathematics Self-Teaching Guide Wiley-Interscience publication |
| Authors | Adi Ben-Israel, A. Ben-Tal, S. Zlobec |
| Edition | illustrated |
| Publisher | Wiley, 1981 |
| Original from | the University of California |
| Digitized | Mar 14, 2008 |
| ISBN | 0471080578, 9780471080572 |
| Length | 144 pages |
| Subjects | › Mathematical optimization Mathematics / Linear & Nonlinear Programming Nonlinear programming |
| Export Citation | BiBTeX EndNote RefMan |