This book provides a comprehensive introduction to the theory and methods of mixed integer nonlinear programming (MINLP). It covers the fundamental concepts, algorithms, and applications of MINLP, a powerful mathematical framework for solving complex optimization problems that involve both continuous and discrete variables, as well as nonlinear objective functions and constraints. The text is designed for graduate students and researchers in operations research, applied mathematics, and computer science.

The book is recognized as a thorough and authoritative treatment of mixed integer nonlinear programming. Its detailed coverage of theoretical underpinnings and algorithmic approaches makes it a valuable resource for advanced students and practitioners. The inclusion of diverse applications highlights the practical relevance and broad applicability of MINLP techniques in various scientific and engineering domains.