000			01398nam a2200181 4500
001			20561141
010			_a 2018014044
020			_a9780000988935
082	0	0	_a519.6 _bYON/O
100	1		_aYong, J
245	1	0	_aOptimization theory : _ba concise introduction
260			_aSingapore _bWorld Scientific _c2020
300			_ax, 223 p. _billustrations ;
520			_a"Mathematically, most of the interesting optimization problems can be formulated to optimize some objective function, subject to some equality and/or inequality constraints. This book introduces some classical and basic results of optimization theory, including nonlinear programming with Lagrange multiplier method, the Karush-Kuhn-Tucker method, Fritz John's method, problems with convex or quasi-convex constraints, and linear programming with geometric method and simplex method. A slim book such as this which touches on major aspects of optimization theory will be very much needed for most readers. We present nonlinear programming, convex programming, and linear programming in a self-contained manner. This book is for a one-semester course for upper level undergraduate students or first/second year graduate students. It should also be useful for researchers working on many interdisciplinary areas other than optimization"--
650		0	_aMathematical optimization.
650		0	_aMathematical analysis.
942			_cBK
999			_c66896 _d66896