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＜電子ブック＞
Large-Scale Optimization with Applications : Part I: Optimization in Inverse Problems and Design / edited by Lorenz T. Biegler, Thomas F. Coleman, Andrew R. Conn, Fadil N. Santosa
(The IMA Volumes in Mathematics and its Applications. ISSN:21983224 ; 92)

版	1st ed. 1997.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	1997
本文言語	英語
大きさ	XV, 204 p : online resource
著者標目	Biegler, Lorenz T editor Coleman, Thomas F editor Conn, Andrew R editor Santosa, Fadil N editor SpringerLink (Online service)
件　名	LCSH:Mathematical optimization LCSH:Calculus of variations LCSH:System theory LCSH:Control theory LCSH:Numerical analysis LCSH:Operations research FREE:Calculus of Variations and Optimization FREE:Systems Theory, Control FREE:Numerical Analysis FREE:Operations Research and Decision Theory
一般注記	Large-Scale Optimization with Applications, Part I: Optimization in Inverse Problems and Design -- Space mapping optimization for engineering design -- An inverse problem in plasma physics: The identification of the current density profile in a Tokamak -- Duality for inverse problems in wave propagation -- Piecewise differentiable minimization for ill-posed inverse problems -- The use of optimization in the reconstruction of obstacles from acoustic or electromagnetic scattering data -- Design of 3D-reflectors for near field and far field problems -- Optimal die shape and ram velocity design for metal forging -- Eigenvalues in optimum structural design -- Optimization Issues in Ocean Acoustics -- Gradient methods in inverse acoustic and electromagnetic scattering -- Atmospheric data assimilation based on the reduced Hessian successive quadratic programming algorithm Inverse problems and optimal design have come of age as a consequence of the availability of better, more accurate, and more efficient simulation packages. Many of these simulators, which can run on small workstations, can capture the complicated behavior of the physical systems they are modeling, and have become commonplace tools in engineering and science. There is a great desire to use them as part of a process by which measured field data are analyzed or by which design of a product is automated. A major obstacle in doing precisely this is that one is ultimately confronted with a large-scale optimization problem. This volume contains expository articles on both inverse problems and design problems formulated as optimization. Each paper describes the physical problem in some detail and is meant to be accessible to researchers in optimization as well as those who work in applied areas where optimization is a key tool. What emerges in the presentations is that there are features about the problem that must be taken into account in posing the objective function, and in choosing an optimization strategy. In particular there are certain structures peculiar to the problems that deserve special treatment, and there is ample opportunity for parallel computation. THIS IS BACK COVER TEXT!!! Inverse problems and optimal design have come of age as a consequence of the availability of better, more accurate, and more efficient, simulation packages. The problem of determining the parameters of a physical system from HTTP:URL=https://doi.org/10.1007/978-1-4612-1962-0

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