Parameterized Algorithms for MILPs with Small Treedepth

Authors: Cornelius Brand, Martin Koutecký, Sebastian Ordyniak12249-12257

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Reproducibility Variable Result LLM Response
Research Type Theoretical In this paper, we extend this line of work to the mixed case, by showing an algorithm solving MILP in time f(a, d) poly(n), where a is the largest coefficient of the constraint matrix, d is its treedepth, and n is the number of variables. This is enabled by proving bounds on the denominators (fractionality) of the vertices of bounded-treedepth (non-integer) linear programs.
Researcher Affiliation Academia Cornelius Brand,1 Martin Kouteck y,1 Sebastian Ordyniak,2 1 Computer Science Institute, Charles University, Prague, Czech Republic, 2 School of Computing, University of Leeds, United Kingdom
Pseudocode No The paper does not contain any structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide any statement or link regarding the availability of open-source code for the described methodology.
Open Datasets No The paper is theoretical and does not use or reference any datasets.
Dataset Splits No The paper is theoretical and does not discuss dataset splits for training, validation, or testing.
Hardware Specification No The paper is theoretical and does not mention any specific hardware used for experiments.
Software Dependencies No The paper is theoretical and does not mention any software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe an experimental setup or hyperparameters.