Inhaltsangabe
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.
Reseña del editor
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.
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