000			01693cam a22002657a 4500
008			130813s2013 si a b 001 0 eng d
020			_a9789814412513
020			_a9814412511
020			_a9789814452762
020			_a9814452769
040			_aSDU
050	0	0	_aQA331.5 _bL295 U 2013
100	1		_aLauritzen, Niels, _9193048
245	1	0	_aUndergraduate convexity : _bfrom Fourier and Motzkin to Kuhn and Tucker.
260			_aSingapore ; _aHackensack, NJ : _bWorld Scientific, _c2013.
300			_a283 p. : _bill.
505	0		_a1. Fourier-Motzkin elimination -- 2. Affine subspaces -- 3. Convex subsets -- 4. Polyhedra -- 5. Computations with polyhedra -- 6. Closed convex subsets and separating hyperplanes -- 7. Convex functions -- 8. Differentiable functions of several variables -- 9. Convex functions of several variables -- 10. Convex optimization -- Appendices.
505	0		_aHKBU library
518			_aYT2025 M08
520	3		_aBased 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 -- P. [4] of cover.
650		0	_aConvex functions.
650		0	_aConvex domains. _9193050
900			_a= C.1 SDU
942			_cGBE _2lcc
999			_c103949 _d103949