目录 Chapter 1 Optimization Models 1.1 Design Optimization 1.1.1 Mathematical Model 1.1.2 Design Optimization Model 1.2 Elements of Optimization Models 1.2.1 Design Variable 1.2.2 Design Constraint 1.2.3 Objective Function 1.2.4 Optimization Model 1.3 Geometric Interpretation of Optimization 1.3.1 Objective Function and Its Contour 1.3.2 Feasible Domain 1 3.3 Activity 1.3.4 Local and Global Optima 1.4 Ideas of Solving Optimization Problem 1.4.1 Analytical Method of Optimization I.4.2 Iterative Method of Optimization 1.4.3 Iterative Termination Criteria Problems Chapter 2 Introduction to MATLAB 2.1 The MATLAB Environment 2.1.1 MATLAB Windows 2.1.2 MATLAB Operators 2.2 Vectors and Matrices 2.3 2D and 3D Graphics 2 3.1 2D Graphics 2.3.2 3D Graphics 2.4 Function Creation Problems Chapter 3 Mathematical Basis of Optimization Design 3.1 Directional Derivatives and Gradients of Multivariate Functions 3.1 1 Directional Derivative 3.1.2 Gradients of Binary Function 3 1.3 Gradients of Multivariate Function 3.2 Taylor Expansion of Multivariate Function 3.3 Extreme Conditions of Unconstrained Optimization Problem 3.3.1 Function With One Variable 3.3.2 Function With n Variables 3.4 Convexity of Function 3.4.1 Convex Set 3.4.2 Convex Function 3.4.3 Convex Programming 3.5 Extreme Conditions of Equality Constrained Optimization Problem 3.5.1 Elimination Method 3.5.2 Lagrangian Multiplier Method 3.6 Extreme Conditions of Inequality Constrained Optimization Problem Problems Chapter 4 One-Dimensional Search Method 4.1 Introduction 4 2 Search Interval and Interval Elimination 4.2.1 Extrapolation Method of Determining Search Interval 4.2.2 Principle of Interval Elimination 4.3 Golden Section Method 4.4 Interpolation Method 4.4.1 Newton Method 4.4.2 Quadratic Interpolation Method 4.5 One-Dimensional Optimization in MATLAB Problems Chapter 5 Interior Optimization 5.1 Introduction 5.2 Gradient Method 5.2 .| Principle 5.2 2 Example 5.2.3 Characteristics 5 3 Newton Method 5.3.1 Principle 5.3.2 Example 5 3.3 Characteristics 5.4 Quasi-Newton Method 5.4.1 Principle 5.4.2 Generate Variable Metric Matrix 5.4.3 DFPandBFGS 5.4.4 Example 5 5 Interior Optimization in MATLAB 5.5.1 Unconstrained Optimization Functions 5.5 2 Graphical Solution 5.5.3 Notes for MATIAB Functions Problems Chapter 6 Boundary Optimization 6 1 Introduction 6.2 Method of a Feasible Direction 6.2.1 Search Strategy 6.2.2 Conditions of a Feasible Direction 6.2.3 Generate a Feasible Direction 6 2 4 Example 6 3 Complex Method 6.3.1 Searching Strategy 6 3.2 Initial Complex Formation 6.3 3 Searching Way in Complex Method 6.3 4 Example 6.4 Penalty Function Method 6.4.1 Principle 6.4.2 Interior-point Penalty Function Method 6.4.3 Exterior-point Penalty Function Method 6.4.4 Mixed Penalty Function Method 6.4.5 Summary 6.5 Boundary Optimization in MATLAB 6.5.1 Constrained Multi-Variable Linear Programming 6.5.2 Constrained Multi-Variable Non-Linear Programming Problems Chapter 7 Modern Optimization Methods 7.1 Genetic Algorithm 7.1.1 Principle 7.1.2 Basic Structure 7.1.3 GA Optimization in MATLAB 7.1.4 Characteristics 7.2 Simulated Annealing 7.2.1 Principle 7.2.2 Procedure 7.2.3 SA Optimization in MATLAB 7.2.4 Characteristics Problems Chapter 8 Introduction to Other Design Methods 8.1 Finite Element Analysis 8.1.1 Basic Idea and Application Field 8.1.2 Basic Steps to Solve Problems 8.1.3 Several Problems 8.1.4 FEA Software 8.2 Innovative Design and TRIZ 8.2
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