Revisiting some classical linearizations of the quadratic binary optimization problem

Fuente: arXiv
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Auteurs principaux: Punnen, Abraham P., Kaur, Navpreet
Format: Preprint
Publié: 2024
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author Punnen, Abraham P.
Kaur, Navpreet
author_facet Punnen, Abraham P.
Kaur, Navpreet
contents In this paper, we present several new linearizations of a quadratic binary optimization problem (QBOP), primarily using the method of aggregations. Although aggregations were studied in the past in the context of solving system of Diophantine equations in non-negative variables, none of the approaches developed produced practical models, particularly due to the large size of associate multipliers. Exploiting the special structure of QBOP we show that selective aggregation of constraints provide valid linearizations with interesting properties. For our aggregations, multipliers can be any non-zero real numbers. Moreover, choosing the multipliers appropriately, we demonstrate that the resulting LP relaxations have value identical to the corresponding non-aggregated models. We also provide a review of existing explicit linearizations of QBOP and presents the first systematic study of such models. Theoretical and experimental comparisons of new and existing models are also provided.
format Preprint
id arxiv_https___arxiv_org_abs_2404_09437
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Revisiting some classical linearizations of the quadratic binary optimization problem
Punnen, Abraham P.
Kaur, Navpreet
Discrete Mathematics
Optimization and Control
In this paper, we present several new linearizations of a quadratic binary optimization problem (QBOP), primarily using the method of aggregations. Although aggregations were studied in the past in the context of solving system of Diophantine equations in non-negative variables, none of the approaches developed produced practical models, particularly due to the large size of associate multipliers. Exploiting the special structure of QBOP we show that selective aggregation of constraints provide valid linearizations with interesting properties. For our aggregations, multipliers can be any non-zero real numbers. Moreover, choosing the multipliers appropriately, we demonstrate that the resulting LP relaxations have value identical to the corresponding non-aggregated models. We also provide a review of existing explicit linearizations of QBOP and presents the first systematic study of such models. Theoretical and experimental comparisons of new and existing models are also provided.
title Revisiting some classical linearizations of the quadratic binary optimization problem
topic Discrete Mathematics
Optimization and Control
url https://arxiv.org/abs/2404.09437