Description

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 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.