Global Optimization Deterministic Approaches

This study develops a unifying approach to constrained global optimization. It provides insight into the underlying concepts and properties of diverse techniques recently proposed to solve a wide variety of problems encountered in the decision sciences, engineering, operations research and other disciplines. As well as a coherent view of the field, new material is presented. The exposition focuses on: minimization of concave functions subject to linear and convex constraints; minimization over the intersection of convex sets and complements of convex sets; global optimization of functions that can be expressed as a difference of two convex functions; Lipschitz and continuous optimization, and systems of equations/inequalities. Additional details on specially structured problems include decomposition of large scale optimization, projection, quadratic, bilinear and biconvex programming, complementarity, separability, parametric approaches, network problems and design centering.