Click Here to Download: https://ouo.io/3giMoM Undergraduate Convexity From Fourier and Motzkin to Kuhn and Tucker By: Niels Lauritzen Publisher: WSPC Print ISBN: 9789814452762, 9814452769 eText ISBN: 9789814412537, 9814412538 Pages: 300 Format: EPUB Available from $ 36.00 USD SKU 9789814412537 Based on undergraduate teaching to students in computer science, economics and mathematics at Aarhus University, this is an elementary introduction to convex sets and convex functions with emphasis on concrete computations and examples. Starting from linear inequalities and Fourier–Motzkin elimination, the theory is developed by introducing polyhedra, the double description method and the simplex algorithm, closed convex subsets, convex functions of one and several variables ending with a chapter on convex optimization with the Karush–Kuhn–Tucker conditions, duality and an interior point algorithm. Contents: Fourier–Motzkin Elimination Affine Subspaces Convex Subsets Polyhedra Computations with Polyhedra Closed Convex Subsets and Separating Hyperplanes Convex Functions Differentiable Functions of Several Variables Convex Functions of Several Variables Convex Optimization Appendices: Analysis Linear (In)dependence and the Rank of a Matrix Readership: Undergraduates focusing on convexity and optimization.
