Entropy Optimization and Mathematical Programming [electronic resource] /

Entropy optimization is a useful combination of classical engineering theory (entropy) with mathematical optimization. The resulting entropy optimization models have proved their usefulness with successful applications in areas such as image reconstruction, pattern recognition, statistical inference, queuing theory, spectral analysis, statistical mechanics, transportation planning, urban and regional planning, input-output analysis, portfolio investment, information analysis, and linear and nonlinear programming. While entropy optimization has been used in different fields, a good number of applicable solution methods have been loosely constructed without sufficient mathematical treatment. A systematic presentation with proper mathematical treatment of this material is needed by practitioners and researchers alike in all application areas. The purpose of this book is to meet this need. Entropy Optimization and Mathematical Programming offers perspectives that meet the needs of diverse user communities so that the users can apply entropy optimization techniques with complete comfort and ease. With this consideration, the authors focus on the entropy optimization problems in finite dimensional Euclidean space such that only some basic familiarity with optimization is required of the reader.

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Bibliographic Details
Main Authors: Fang, S.-C. author., Rajasekera, J. R. author., Tsao, H.-S. J. author., SpringerLink (Online service)
Format: Texto biblioteca
Language:eng
Published: Boston, MA : Springer US : Imprint: Springer, 1997
Subjects:Business., Operations research., Decision making., Mathematical optimization., Calculus of variations., Business and Management., Operation Research/Decision Theory., Calculus of Variations and Optimal Control; Optimization., Optimization.,
Online Access:http://dx.doi.org/10.1007/978-1-4615-6131-6
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id KOHA-OAI-TEST:184264
record_format koha
institution COLPOS
collection Koha
country México
countrycode MX
component Bibliográfico
access En linea
En linea
databasecode cat-colpos
tag biblioteca
region America del Norte
libraryname Departamento de documentación y biblioteca de COLPOS
language eng
topic Business.
Operations research.
Decision making.
Mathematical optimization.
Calculus of variations.
Business and Management.
Operation Research/Decision Theory.
Calculus of Variations and Optimal Control; Optimization.
Optimization.
Business.
Operations research.
Decision making.
Mathematical optimization.
Calculus of variations.
Business and Management.
Operation Research/Decision Theory.
Calculus of Variations and Optimal Control; Optimization.
Optimization.
spellingShingle Business.
Operations research.
Decision making.
Mathematical optimization.
Calculus of variations.
Business and Management.
Operation Research/Decision Theory.
Calculus of Variations and Optimal Control; Optimization.
Optimization.
Business.
Operations research.
Decision making.
Mathematical optimization.
Calculus of variations.
Business and Management.
Operation Research/Decision Theory.
Calculus of Variations and Optimal Control; Optimization.
Optimization.
Fang, S.-C. author.
Rajasekera, J. R. author.
Tsao, H.-S. J. author.
SpringerLink (Online service)
Entropy Optimization and Mathematical Programming [electronic resource] /
description Entropy optimization is a useful combination of classical engineering theory (entropy) with mathematical optimization. The resulting entropy optimization models have proved their usefulness with successful applications in areas such as image reconstruction, pattern recognition, statistical inference, queuing theory, spectral analysis, statistical mechanics, transportation planning, urban and regional planning, input-output analysis, portfolio investment, information analysis, and linear and nonlinear programming. While entropy optimization has been used in different fields, a good number of applicable solution methods have been loosely constructed without sufficient mathematical treatment. A systematic presentation with proper mathematical treatment of this material is needed by practitioners and researchers alike in all application areas. The purpose of this book is to meet this need. Entropy Optimization and Mathematical Programming offers perspectives that meet the needs of diverse user communities so that the users can apply entropy optimization techniques with complete comfort and ease. With this consideration, the authors focus on the entropy optimization problems in finite dimensional Euclidean space such that only some basic familiarity with optimization is required of the reader.
format Texto
topic_facet Business.
Operations research.
Decision making.
Mathematical optimization.
Calculus of variations.
Business and Management.
Operation Research/Decision Theory.
Calculus of Variations and Optimal Control; Optimization.
Optimization.
author Fang, S.-C. author.
Rajasekera, J. R. author.
Tsao, H.-S. J. author.
SpringerLink (Online service)
author_facet Fang, S.-C. author.
Rajasekera, J. R. author.
Tsao, H.-S. J. author.
SpringerLink (Online service)
author_sort Fang, S.-C. author.
title Entropy Optimization and Mathematical Programming [electronic resource] /
title_short Entropy Optimization and Mathematical Programming [electronic resource] /
title_full Entropy Optimization and Mathematical Programming [electronic resource] /
title_fullStr Entropy Optimization and Mathematical Programming [electronic resource] /
title_full_unstemmed Entropy Optimization and Mathematical Programming [electronic resource] /
title_sort entropy optimization and mathematical programming [electronic resource] /
publisher Boston, MA : Springer US : Imprint: Springer,
publishDate 1997
url http://dx.doi.org/10.1007/978-1-4615-6131-6
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spelling KOHA-OAI-TEST:1842642018-07-30T23:06:06ZEntropy Optimization and Mathematical Programming [electronic resource] / Fang, S.-C. author. Rajasekera, J. R. author. Tsao, H.-S. J. author. SpringerLink (Online service) textBoston, MA : Springer US : Imprint: Springer,1997.engEntropy optimization is a useful combination of classical engineering theory (entropy) with mathematical optimization. The resulting entropy optimization models have proved their usefulness with successful applications in areas such as image reconstruction, pattern recognition, statistical inference, queuing theory, spectral analysis, statistical mechanics, transportation planning, urban and regional planning, input-output analysis, portfolio investment, information analysis, and linear and nonlinear programming. While entropy optimization has been used in different fields, a good number of applicable solution methods have been loosely constructed without sufficient mathematical treatment. A systematic presentation with proper mathematical treatment of this material is needed by practitioners and researchers alike in all application areas. The purpose of this book is to meet this need. Entropy Optimization and Mathematical Programming offers perspectives that meet the needs of diverse user communities so that the users can apply entropy optimization techniques with complete comfort and ease. With this consideration, the authors focus on the entropy optimization problems in finite dimensional Euclidean space such that only some basic familiarity with optimization is required of the reader.1 Introduction to Entropy and Entropy Optimization Principles -- 1.1 Introduction to Finite-Dimensional Entropy -- 1.2 Entropy Optimization Problems -- References -- 2 Entropy Optimization Models -- 2.1 Queueing Theory -- 2.2 Transportation Planning -- 2.3 Input-Output Analysis -- 2.4 Regional Planning -- 2.5 Portfolio Optimization -- 2.6 Image Reconstruction -- References -- 3 Entropy Optimization Methods: Linear Case -- 3.1 Existing Methods -- 3.2 An Unconstrained Convex Programming Approach -- 3.3 Entropy Optimization Problems with Infinitely Many Linear Constraints -- References -- 4 Entropy Optimization Methods: General Convex Case -- 4.1 Existing Methods -- 4.2 Entropy Optimization with Quadratic Constraints -- 4.3 Entropy Optimization with Entropic Constraints -- 4.4 Entropy Optimization with Convex Constraints -- References -- 5 Entropic Perturbation Approach to Mathematical Programming -- 5.1 Linear Programming: Karmarkar-Form -- 5.2 Linear Programming: Standard-Form -- 5.3 Convex Quadratic Programming -- 5.4 Linear and Convex Quadratic Semi-infinite Programming -- References -- 6 Lp-Norm Perturbation Approach: A Generalization of Entropic Perturbation -- 6.1 Perturbing the Dual Feasible Region of Standard-form Linear Programs -- 6.2 Solving Linear Programs with Inequality Constraints via Perturbation of Feasible Region -- 6.3 Perturbing Dual Feasible Region of Convex Quadratic Programs -- References -- 7 Extensions and Related Results -- 7.1 Entropy Optimization with Countably Many Variables -- 7.2 Entropy Optimization and Bayesian Statistical Estimation -- 7.3 Entropic Regularization for Min-Max Problems -- 7.4 Semi-Infinite Min-Max Problems -- References.Entropy optimization is a useful combination of classical engineering theory (entropy) with mathematical optimization. The resulting entropy optimization models have proved their usefulness with successful applications in areas such as image reconstruction, pattern recognition, statistical inference, queuing theory, spectral analysis, statistical mechanics, transportation planning, urban and regional planning, input-output analysis, portfolio investment, information analysis, and linear and nonlinear programming. While entropy optimization has been used in different fields, a good number of applicable solution methods have been loosely constructed without sufficient mathematical treatment. A systematic presentation with proper mathematical treatment of this material is needed by practitioners and researchers alike in all application areas. The purpose of this book is to meet this need. Entropy Optimization and Mathematical Programming offers perspectives that meet the needs of diverse user communities so that the users can apply entropy optimization techniques with complete comfort and ease. With this consideration, the authors focus on the entropy optimization problems in finite dimensional Euclidean space such that only some basic familiarity with optimization is required of the reader.Business.Operations research.Decision making.Mathematical optimization.Calculus of variations.Business and Management.Operation Research/Decision Theory.Calculus of Variations and Optimal Control; Optimization.Optimization.Springer eBookshttp://dx.doi.org/10.1007/978-1-4615-6131-6URN:ISBN:9781461561316