LRAMBO

The NEOS Server offers LRAMBO for the solution of nonlinear optimization problems with equality and inequality constraints.

The approach to solve nonlinear constrained optimization problems in LRAMBO is 'total quasi-Newton' with linesearch and a working set strategy. The 'total quasi-Newton' approach combines the selective evaluation of cheaply available derivatives via Algorithmic Differentiation (AD) with the approximation of the Jacobian and Hessian matrices by new, linearly invariant update formulas. As a result the linear algebra cost per iteration is only quadratic with respect to n+m, and the evaluation effort is bounded by a small multiple of that needed to compute the objective and derivative values by themselves. Due to the heredity property of the updates equality constrained quadratic programs are solved exactly in n steps for almost all initializations of primal and dual variables as well as Jacobian and Hessian approximations.

LRAMBO is being developed as part of the research project "General purpose, Linearly Invariant Algorithm for Large-Scale Nonlinear Programming".

The authors of LRAMBO are: Andreas Griewank, Stefan Körkel, Kshitij Kulshreshtha, Torsten Bosse, Volker Schloßhauer, and Lars Sadau.

It is based on previous work by: Andrea Walther, Andrej Ponomarenko, Maciek Korzec, Sascha Eichstädt, and Susanne Kreiterling.

The solver requires the input of evaluation routines for the objective, an initial point, and the constraints. First and second order derivatives can be computed by automatic differentiation with ADOL-C.

The solver setup was last updated by J.Utke on Jul/07/09 for Adol-C v 2.0.

Using the NEOS Server for LRAMBO

To solve a problem, the user must submit to the server:

The number of variables
A subroutine that defines the starting point
A subroutine that defines the constraints
A subroutine that evaluates the objective function

How many variables are in your problem
Number of dimensions:

How many equality contraints do you have
Number of equality constraints:

How many contraints do you have altogether
Number of all constraints:

AD tool:

In what file is the function to evaluate the objective? Your function must be called 'fcn' and have this prototype.

void fcn(int ndim, double *x, double *f)

Evaluate function (local file):

In what file is the function to set the constraints? The function must be called 'constrs' and have this prototype:

void constrs(int ndim, double *x, int meq, int mup, double *c)

int *ndim -- # of dimensions in the problem

double *x -- variables
double *c -- constraints

Set constraints (local file):

In what file is the function to set the initial vector? The function must be called 'initpt' and have this prototype:

void initpt(int ndim, double *x)

int *ndim -- # of dimensions in the problem
double *x -- the initial vector

Initial Value Function:

Comments:

e-mail address:

Please do not click the 'Submit to NEOS' button more than once.

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