Difference between revisions of "MIPDECO"

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=== Laplace Source Inversion ===
 
=== Laplace Source Inversion ===
  
Problem is to identify source to match an observed state, <math> \bar u </math>, governed by Laplace equation with Dirichtlet boundary conditions:
+
Problem is to identify source to match an observed state, governed by Laplace equation with Dirichtlet boundary conditions.
{| align="center"
 
| minimize    || <math> \int_{\Omega} u - \bar u d\Omega</math>      ||
 
|-
 
| subject to  || <math>g_i(x,y)  \leq 0 \,</math> || for <math>i = 1, ..., m \,</math>
 
|-
 
|                  || <math> x \in X \; y \in Y</math> integer, ||
 
|}
 
  
 
=== Distributed Control with Neumann Boundary Conditions ===
 
=== Distributed Control with Neumann Boundary Conditions ===

Revision as of 17:08, 2 August 2016

Mixed-Integer PDE Constrained Optimization (MIPDECO) Test Problems

This page links to sets of MIPDECO test problems written in AMPL and described in a companion report.

Each problem includes a characterization in terms of type of PDE, class of integers, type of objective, type of constraints, and discretization scheme.

A tar-ball with all ampl models, data, and command files is available here. A tar-ball with the corresponding stub.nl files is available here.

Laplace Source Inversion

Problem is to identify source to match an observed state, governed by Laplace equation with Dirichtlet boundary conditions.

Distributed Control with Neumann Boundary Conditions

Parabolic Robin Boundary Problem in One Dimension

Parabolic Robin Boundary Problem in Two Dimensions

Heat Equation Actuator-Placement

Subsurface Flow Well-Placement