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Up-> CppAD ADFun abs_normal

CppAD-> Install Introduction AD ADFun preprocessor multi_thread utility ipopt_solve Example speed Appendix

ADFun-> record_adfun drivers Forward Reverse sparsity_pattern sparse_derivative optimize abs_normal FunCheck check_for_nan

abs_normal-> abs_normal_fun abs_print_mat abs_eval simplex_method lp_box abs_min_linear min_nso_linear qp_interior qp_box abs_min_quad min_nso_quad

Headings-> Reference Contents

@(@\newcommand{\W}[1]{ \; #1 \; } \newcommand{\R}[1]{ {\rm #1} } \newcommand{\B}[1]{ {\bf #1} } \newcommand{\D}[2]{ \frac{\partial #1}{\partial #2} } \newcommand{\DD}[3]{ \frac{\partial^2 #1}{\partial #2 \partial #3} } \newcommand{\Dpow}[2]{ \frac{\partial^{#1}}{\partial {#2}^{#1}} } \newcommand{\dpow}[2]{ \frac{ {\rm d}^{#1}}{{\rm d}\, {#2}^{#1}} }@)@Abs-normal Representation of Non-Smooth Functions
Reference
Andreas Griewank, Jens-Uwe Bernt, Manuel Radons, Tom Streubel, Solving piecewise linear systems in abs-normal form, Linear Algebra and its Applications, vol. 471 (2015), pages 500-530.

Contents

abs_normal_fun	Create An Abs-normal Representation of a Function
abs_print_mat	abs_normal: Print a Vector or Matrix
abs_eval	abs_normal: Evaluate First Order Approximation
simplex_method	abs_normal: Solve a Linear Program Using Simplex Method
lp_box	abs_normal: Solve a Linear Program With Box Constraints
abs_min_linear	abs_normal: Minimize a Linear Abs-normal Approximation
min_nso_linear	Non-Smooth Optimization Using Abs-normal Linear Approximations
qp_interior	Solve a Quadratic Program Using Interior Point Method
qp_box	abs_normal: Solve a Quadratic Program With Box Constraints
abs_min_quad	abs_normal: Minimize a Linear Abs-normal Approximation
min_nso_quad	Non-Smooth Optimization Using Abs-normal Quadratic Approximations

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Input File: example/abs_normal/abs_normal.omh