Output Headings: Large-Scale algorithms Optimization of Inline Objects Instead of M-Files 2-74 Typical Problems and How to Deal with Them 276 Converting Your Code to Version 2 Syntax U t and optimget New Calling Sequences Example of Converting from constr to fmincon Selected Bibliography 2-92 Standard Algorithms 3 Optimization Overview Unconstrained Optimization Quasi-Newton Methods 36 Line search 38 Quasi-Newton Implementation Least-Squares Optimization 3-18 Gauss-Newton method 3-19 Levenberg- Marquardt Method Nonlinear Least-Squares Implementation Nonlinear Systems of Equations 3-24 Method 3-24 Trust-Region Dogleg Method 3-24 Nonlinear Equations Implementation Constrained Optimization .... 3-28 Sequential quadratic Programming(SQP) quadratic Programming(QP) Subproblem SQP Implementatieiii Output Headings: Large-Scale Algorithms . . . . . . . . . . . . . . . 2-71 Optimization of Inline Objects Instead of M-Files . . . . . . . 2-74 Typical Problems and How to Deal with Them . . . . . . . . . . 2-76 Converting Your Code to Version 2 Syntax . . . . . . . . . . . . . 2-80 Using optimset and optimget . . . . . . . . . . . . . . . . . . . . . . . . . . 2-81 New Calling Sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-81 Example of Converting from constr to fmincon . . . . . . . . . . . . 2-89 Selected Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-92 3 Standard Algorithms Optimization Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 Unconstrained Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 Quasi-Newton Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-6 Line Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-8 Quasi-Newton Implementation . . . . . . . . . . . . . . . . . . . . . . . . . 3-11 Least-Squares Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-18 Gauss-Newton Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-19 Levenberg-Marquardt Method . . . . . . . . . . . . . . . . . . . . . . . . . 3-20 Nonlinear Least-Squares Implementation . . . . . . . . . . . . . . . . 3-22 Nonlinear Systems of Equations . . . . . . . . . . . . . . . . . . . . . . . 3-24 Gauss-Newton Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-24 Trust-Region Dogleg Method . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-24 Nonlinear Equations Implementation . . . . . . . . . . . . . . . . . . . 3-26 Constrained Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-28 Sequential Quadratic Programming (SQP) . . . . . . . . . . . . . . . 3-29 Quadratic Programming (QP) Subproblem . . . . . . . . . . . . . . . 3-30 SQP Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-31