Optimization: principles and algorithms, by Michel Bierlaire
run1905.m
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1 %> \file
2 %> Runs example 19.5 with the augmented lagrangian method of \cite Bier15-book
3 %>
4 %> @note Calls \ref augmentedLagrangian
5 %>
6 %> @remark The implementation of the augmented Lagrangian method called by this example is slightly different from the implementation used to generate Tables 19.1 and 19.2, so that the iterates are not the same.
7 %>
8 %> @ingroup Running
9 %> @ingroup chap19
10 %> @author Michel Bierlaire
11 %> @date Mon Mar 23 16:41:47 2015
12 
13 x0 = [-1 ; 0.1] ;
14 lambda0 = 0 ;
15 eps = 1.0e-11 ;
16 [solution,lambda] = augmentedLagrangian('ex1905',x0,lambda0,eps,1000)
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augmentedLagrangian
function augmentedLagrangian(in problem, in x0, in lambda0, in eps, in maxiter)
Applies the augmented Lagrangian method to solve subject to where and .
Copyright 2015-2018 Michel Bierlaire