Applied Optimization with MATLAB Programming, 2/e (Hardcover)

Description
Over the last few decades, optimization techniques have been streamlined by the use of computers and artificial intelligence methods to analyze more variables (especially under non-linear, multivariable conditions) more quickly than ever before. This book covers all classical linear and nonlinear optimization techniques while focusing on the standard mathematical engine, MATLAB. As with the first edition, the author uses MATLAB in examples for running computer-based optimization problems. New coverage in this edition includes design optimization techniques such as Multidisciplinary Optimization, Explicit Solution for Boundary Value Problems, and Particle Swarm Optimization.

Table of Contents
Chapter 1: Introduction.
Chapter 2: Graphical Optimization.
Chapter 3: Linear Programming.
Chapter 4: Nonlinear Programming.
Chapter 5: Numerical Techniques - The One Dimensional Problem.
Chapter 6: Numerical Techniques for Unconstrained Optimization.
Chapter 7: Numerical Techniques for Constrained Optimization.
Chapter 8: Discrete Optimization.
Chapter 9: Global Optimization.
Chapter 10: Optimization Toolbox from MATLAB.
Chapter 11: Hybrid Mathematics: An Application of.

在過去幾十年中，優化技術已經通過使用計算機和人工智能方法來分析更多變數（尤其是在非線性、多變量條件下）比以往更快速。本書涵蓋了所有經典的線性和非線性優化技術，並專注於標準的數學引擎MATLAB。與第一版一樣，作者在示例中使用MATLAB來運行基於計算機的優化問題。本版新增的內容包括設計優化技術，如多學科優化、邊界值問題的顯式解和粒子群優化。

目錄：
第1章：介紹。
第2章：圖形優化。
第3章：線性規劃。
第4章：非線性規劃。
第5章：數值技術-一維問題。
第6章：無約束優化的數值技術。
第7章：約束優化的數值技術。
第8章：離散優化。
第9章：全局優化。
第10章：MATLAB的優化工具箱。
第11章：混合數學：一個應用實例。