Large-Scale Optimization with Applications: Optimization in Inverse Problems and Design
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Many important molecular conformation problems, such as protein folding, are expressed as global minimization problems. It is the fact that local minimization is insufficient, that markedly differentiates this volume from the previous two. Unfortunately, global minimization problems that result from models of molecular conformation are usually intractable. For example, simple 1-dimensional versions of distance conformation problems are NP-hard. Nevertheless, there has been significant recent progress in the design of promising heuristic strategies (often involving the use of high- performance parallel computers) for computing approximate global minimizers. The purpose of the sessions represented in this volume was to discuss the new algorithmic advances for global minimization in the context of protein folding and related molecular minimization problems. Emphasis was on practical shortcomings of current approaches, outstanding problems and questions, and the use of high-performance parallel computers.
ForewordGeneral Preface for Large-Scale Optimization with Applications, Part I, II, and IIIPreface for Part IIContents for Part IContents for Part IIIThe development of the SQP algorithm for nonlinear programming1Some aspects of sequential quadratic programming methods21Computing sparse Hessian and Jacobian approximations with optimal hereditary properties37Experience with a sparse nonlinear programming algorithm53Mixed-integer nonlinear programming: A survey of algorithms and applications73A Multiplier-free, reduced Hessian method for process optimization101Deterministic global optimization in design, control, and computational chemistry129Optimization problems in model predictive control185Some recent developments in computational optimal control203Large-scale structural design optimization235Large-scale SQP methods for optimization of Navier-Stokes flows247Numerical optimal control of parabolic PDEs using DASOPT271The promise (and reality) of multidisciplinary design optimization301
