Textbook in PDF format

This book examines the most fundamental parts of convex analysis and its applications to optimization and location problems. Accessible techniques of variational analysis are employed to clarify and simplify some basic proofs in convex analysis and to build a theory of generalized differentiation for convex functions and sets in finite dimensions. The book serves as a bridge for the readers who have just started using convex analysis to reach deeper topics in the field. Detailed proofs are presented for most of the results in the book and also included are many figures and exercises for better understanding the material. Applications provided include both the classical topics of convex optimization and important problems of modern convex optimization, convex geometry, and facility location.
Convex Sets and Functions
Convex Separation and Some Consequences
Convex Generalized Differentiation
Fenchel Conjugate and Further Topics in Subdifferentiation
Remarkable Consequences of Convexity
Minimal Time Functions and Related Issues
Applications to Problems of Optimization and Equilibrium
Applications to Location Problems