Deterministic Global Optimization

Preface. 1. Introduction. 2. Basic Concepts of Global Optimization. Part I: Biconvex and Bilinear Problems. 3. The GOP Primal-Relaxed Dual Decomposition Approach: Theory. 4. The GOP Approach: Implementation and Computational Studies. 5. The GOP Approach in Bilevel Linear and Quadratic Problems. 6. The GOP Approach in Phase and Chemical Equilibrium Problems. 7. The GOP Approach: Distributed Implementation. Part II: Signomial Problems. 8. Generalized Geometric Programming: Theory. 9. Generalized Geometric Programming: Computational Studies. Part III: Towards General Twice Differentiable NLPs. 10. From Biconvex to General Twice Differentiable NLPs. 11. The alphaBB For Box Constrained Twice-Differentiable NLPs: Theory. 12. The alphaBB for Constrained Twice-Differentiable NLPs: Theory. 13. Computational Studies of the alphaBB Approach. 14. Global Optimization in Microclusters. 15. The alphaBB Approach in Molecular Structure Prediction. 16. The alphaBB Approach in Protein Folding. 17. The alphaBB Approach in Peptide Docking. 18. The alphaBB Approach in Batch Design Under Uncertainty. 19. The alphaBB Approach in Parameter Estimation. Part IV: Nonlinear and Mixed-Integer Optimization. 20. Introduction to Nonlinear and Mixed-Integer Optimization. 21. The SMIN-alphaBB Approach: Theory and Computations. 22. The GMIN-alphaBB Approach: Theory and Computations. Part V: Nonlinear Constrained Systems of Equations. 23. All Solutions of Nonlinear Constrained Systems of Equations. 24. Locating all Homogeneous Azeotropes. References. Index.