000			01329nam a2200157 4500
020			_a9780000988935
082			_a519 _bYON/O
100			_aYong, Jiongmin
245			_aOptimization theory: a concise introduction
260			_aNew Jersey _bWorld scientific _c2020
300			_a223 p.
520			_aMathematically, 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 onesemester 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			_aMathematical optimization
650			_aProgramming (Mathematics)
942			_cBK
999			_c64272 _d64272