Titlebook: Entropy Optimization and Mathematical Programming; S.-C. Fang,J. R. Rajasekera,H.-S. J. Tsao Book 1997 Springer Science+Business Media New

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書目名稱Entropy Optimization and Mathematical Programming影響因子(影響力)




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Diuretic

Entropy Optimization Models,, those disciplines include statistical mechanics, thermodynamics, statistical parameter estimation and inference, economics, business and finance, nonlinear spectral analysis, pattern recognition, transportation, urban and regional planning, queueing theory, and linear and nonlinear programming. In

HEW

Entropy Optimization Methods: Linear Case,ion of 0 ln 0 = 0, we define the quantity . to be the cross-entropy of x with respect to ., in a general sense. Note that when x and p are both probability distributions, i.e., . this quantity becomes the commonly defined cross-entropy between the two probability distributions (see Chapter 1).

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Integrate

,,-Norm Perturbation Approach: A Generalization of Entropic Perturbation,ntly in developing interior-point methods [3, 17, 4, 13, 18]. However, the idea of perturbing the feasible region has not been fully explored. This chapter focuses on this idea and discusses a particular approach involving the ..-norm of a vector measure of constraint violation. Three topics will be

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Uranium - Past and Future Challengestion approach by using the entropic function, . for solving four classes of problems, namely, linear programming problems in Karmarkar’s form, linear programming programs in standard form, convex quadratic programming problems, and linear and convex quadratic semi-infinite programming problems.

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Glycogen

Introduction to Entropy and Entropy Optimization Principles,ussed along with references to the existing literature. The chapter consists of two sections. Section 1.1 introduces the concept of entropy, and Section 1.2 classifies different entropy optimization problems to be studied in this book.

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0884-8289 y. .optimization models. have proved theirusefulness with successful applications in areas such as imagereconstruction, pattern recognition, statistical inference, queuingtheory, spectral analysis, statistical mechanics, transportationplanning, urban and regional planning, input-output analysis,port