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Nonlinear Optimization - Fox, William P.

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      Présentation Nonlinear Optimization Format Relié

       - Livre Beaux arts

      Livre Beaux arts - Fox, William P. - 01/12/2020 - Relié - Langue : Anglais

      . .

    • Auteur(s) : Fox, William P.
    • Editeur : Chapman And Hall/Crc
    • Langue : Anglais
    • Parution : 01/12/2020
    • Format : Moyen, de 350g à 1kg
    • Nombre de pages : 418.0
    • Expédition : 757
    • Dimensions : 23.4 x 15.6 x 2.7
    • ISBN : 9780367444150



    • Résumé :
      ..

      Biographie:
      Dr. William P. Fox is a professor in the Department of Defense Analysis at the Naval Postgraduate School and currently teaches a three course sequence in mathematical modeling for decision making. He received his Ph.D. at Clemson University. He has taught at the United States Military Academy and at Francis Marion University where he was the chair of mathematics for eight years. He has many publications and scholarly activities including sixteen books, one hundred and fifty journal articles, and about one hundred and fifty conference presentations, and workshops. He was Past- President of the Military Application Society of INFORMS and is the current Vice Chair for Programs for BIG SIGMAA.

      Sommaire:

      Chapter 1. Nonlinear Optimization Overview

      1.1 Introduction
      1.2 Modeling
      1.3 Exercises

      Chapter 2. Review of Single Variable Calculus Topics
      2.1 Limits
      2.2 Continuity
      2.3 Differentiation
      2.4 Convexity

      Chapter 3. Single Variable Optimization

      3.1 Introduction
      3.2 Optimization Applications
      3.3 Optimization Models
      Constrained Optimization by Calculus

      Chapter 4. Single Variable Search Methods

      4.1 Introduction
      4.2 Unrestricted Search
      4.3 Dichotomous Search
      4.4 Golden Section Search
      4.5 Fibonacci Search
      4.6 Newton?s Method
      4.7 Bisection Derivative Search

      Chapter 5. Review of MV Calculus Topics
      5.1 Introduction, Basic Theory, and Partial Derivatives
      5.2 Directional Derivatives and The Gradient

      Chapter 6. MV Optimization

      6.1 Introduction
      6.2 The Hessian
      6.3 Unconstrained Optimization
      Convexity and The Hessian Matrix
      Max and Min Problems with Several Variables

      Chapter 7. Multi-variable Search Methods

      7.1 Introduction
      7.2 Gradient Search
      7.3 Modified Newton?s Method

      Chapter 8. Equality Constrained Optimization: Lagrange Multipliers

      8.1 Introduction and Theory
      8.2 Graphical Interpretation
      8.3 Computational Methods
      8.4 Modeling and Applications

      Chapter 9. Inequality Constrained Optimization; Kuhn-Tucker Methods

      9.1 Introduction
      9.2 Basic Theory
      9.3 Graphical Interpretation and Computational Methods
      9.4 Modeling and Applications

      Chapter 10. Method of Feasible Directions and Other Special NL Methods

      10.1 Methods of Feasible Directions
      Numerical methods (Directional Searches)
      Starting Point Methods
      10.2 Separable Programming
      10.3 Quadratic Programming

      Chapter 11. Dynamic Programming
      11.1 Introduction
      11.2 Continuous Dynamic Programming
      11.3 Modeling and Applications with Continuous DP
      11.4 Discrete Dynamic Programming
      11.5 Modeling and Applications with Discrete Dynamic Programming

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