Global optimization is a rapidly growing field with powerful applications in applied mathematics and the physical sciences. This book provides a thorough overview of this area, with material on key topics such as complexity; heuristic methods; derivation of lower bounds for minimization problems; and branch and bound methods and convergence. The final chapter offers both benchmark test problems and applications of global optimization such as finding the conformation of a molecule or planning an optimal trajectory for interplanetary space travel. In addition, fundamental information on convex and concave functions is provided in an index. This book is intended for graduate students, researchers, and practitioners looking for advanced solution methods to difficult optimization problems. It is appropriate for use as a supplementary text in an advanced graduate-level seminar.