Optimization: principles and algorithms, by Michel Bierlaire
Functions
localSqp.m File Reference

Algorithm 20.1: local SQP algorithm. More...

Go to the source code of this file.

Functions

function localSqp (in problem, in x0, in lambda0, in eps, in maxiter)
 Applies the local SQP method to solve

\[\min_x f(x) \]

subject to

\[h(x)=0,\]

where $f:\mathbb{R}^n \to \mathbb{R}$ and $h:\mathbb{R}^n \to \mathbb{R}^m $. More...

 

Detailed Description

Algorithm 20.1: local SQP algorithm.

Implementation of algorithm 20.1 of [1]

Note
Tested with run2002.m
Tested with run2003.m
Tested with run2004.m
Author
Michel Bierlaire
Date
Thu Mar 26 13:33:44 2015

Definition in file localSqp.m.

Function Documentation

function localSqp ( in  problem,
in  x0,
in  lambda0,
in  eps,
in  maxiter 
)

Applies the local SQP method to solve

\[\min_x f(x) \]

subject to

\[h(x)=0,\]

where $f:\mathbb{R}^n \to \mathbb{R}$ and $h:\mathbb{R}^n \to \mathbb{R}^m $.

Parameters
problemthe name of the Octave function defining f(x), h(x) and their derivatives. The funtion has two arguments: x and index. If index=0, the objective function $f$ and its derivatives are evaluated. If index= $i$, the constraint $h_i$ and its derivtives are evaluated.
x0starting primal point (nx1)
lambda0starting dual point (mx1)
epsalgorithm stops if $\|\nabla L(x_k,\lambda_k\| \leq \varepsilon $ and $\|h(x_k)\|^2$.
maxitermaximum number of iterations (default: 100)
Returns
[solution,lambda]
x: primal solution
lambda: dual solution
Copyright 2015-2016 Michel Bierlaire