This volume contains a thorough overview of the rapidly growing field of global optimization, with chapters 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. An appendix provides fundamental information on convex and concave functions.
Audience: Global Optimization is intended for Ph.D. students, researchers, and practitioners looking for advanced solution methods to difficult optimization problems. It can be used as a supplementary text in an advanced graduate-level seminar. Contents: Chapter 1: Introduction; Chapter 2: Complexity; Chapter 3: Heuristics; Chapter 4: Lower Bounds; Chapter 5: Branch and Bound; Chapter 6: Problems; Appendix A: Basic Definitions and Results on Convexity; Appendix B: Notation.