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Bibliographic Details
Main Authors: Manns, Paul, Severitt, Marvin
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.09213
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author Manns, Paul
Severitt, Marvin
author_facet Manns, Paul
Severitt, Marvin
contents We analyze integer linear programs which we obtain after discretizing two-dimensional subproblems arising from a trust-region algorithm for mixed integer optimal control problems with total variation regularization. We discuss NP-hardness of the discretized problems and the connection to graph-based problems. We show that the underlying polyhedron exhibits structural restrictions in its vertices with regards to which variables can attain fractional values at the same time. Based on this property, we derive cutting planes by employing a relation to shortest-path and minimum bisection problems. We propose a branching rule and a primal heuristic which improves previously found feasible points. We validate the proposed tools with a numerical benchmark in a standard integer programming solver. We observe a significant speedup for medium-sized problems. Our results give hints for scaling towards larger instances in the future.
format Preprint
id arxiv_https___arxiv_org_abs_2403_09213
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On Discrete Subproblems in Integer Optimal Control with Total Variation Regularization in Two Dimensions
Manns, Paul
Severitt, Marvin
Optimization and Control
90C11, 90C35, 49M37
We analyze integer linear programs which we obtain after discretizing two-dimensional subproblems arising from a trust-region algorithm for mixed integer optimal control problems with total variation regularization. We discuss NP-hardness of the discretized problems and the connection to graph-based problems. We show that the underlying polyhedron exhibits structural restrictions in its vertices with regards to which variables can attain fractional values at the same time. Based on this property, we derive cutting planes by employing a relation to shortest-path and minimum bisection problems. We propose a branching rule and a primal heuristic which improves previously found feasible points. We validate the proposed tools with a numerical benchmark in a standard integer programming solver. We observe a significant speedup for medium-sized problems. Our results give hints for scaling towards larger instances in the future.
title On Discrete Subproblems in Integer Optimal Control with Total Variation Regularization in Two Dimensions
topic Optimization and Control
90C11, 90C35, 49M37
url https://arxiv.org/abs/2403.09213