The Quadratic Bin Packing Problem: Exact Formulations and Algorithm

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Chagas, Vítor Gomes, Locatelli, Alberto, Miyazawa, Flávio Keidi, Iori, Manuel
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866910100501823488
author Chagas, Vítor Gomes
Locatelli, Alberto
Miyazawa, Flávio Keidi
Iori, Manuel
author_facet Chagas, Vítor Gomes
Locatelli, Alberto
Miyazawa, Flávio Keidi
Iori, Manuel
contents In this article, we introduce and study the Quadratic Bin Packing Problem (QBPP), which generalizes the classical bin packing problem by introducing a fixed cost for each used bin and a pairwise cost (or profit) incurred whenever two items are packed together. Beyond its theoretical relevance, the QBPP is of practical interest due to its numerous real-world applications, mainly related to cluster analysis. To address the QBPP, we propose three compact mixed-integer linear programming (MILP) formulations, along with a set-partitioning formulation. For each compact model, we present an enhanced version with a strengthened continuous relaxation, while, for the set-partitioning formulation, we develop a tailored Branch-and-Price algorithm. Computational experiments on benchmark instances demonstrated that, while the enhanced compact formulations can be effectively solved by a standard MILP solver for small-sized instances, the Branch-and-Price approach delivered superior performance overall, especially on larger and more challenging instances.
format Preprint
id arxiv_https___arxiv_org_abs_2604_03078
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle The Quadratic Bin Packing Problem: Exact Formulations and Algorithm
Chagas, Vítor Gomes
Locatelli, Alberto
Miyazawa, Flávio Keidi
Iori, Manuel
Optimization and Control
90C10, 90C11
In this article, we introduce and study the Quadratic Bin Packing Problem (QBPP), which generalizes the classical bin packing problem by introducing a fixed cost for each used bin and a pairwise cost (or profit) incurred whenever two items are packed together. Beyond its theoretical relevance, the QBPP is of practical interest due to its numerous real-world applications, mainly related to cluster analysis. To address the QBPP, we propose three compact mixed-integer linear programming (MILP) formulations, along with a set-partitioning formulation. For each compact model, we present an enhanced version with a strengthened continuous relaxation, while, for the set-partitioning formulation, we develop a tailored Branch-and-Price algorithm. Computational experiments on benchmark instances demonstrated that, while the enhanced compact formulations can be effectively solved by a standard MILP solver for small-sized instances, the Branch-and-Price approach delivered superior performance overall, especially on larger and more challenging instances.
title The Quadratic Bin Packing Problem: Exact Formulations and Algorithm
topic Optimization and Control
90C10, 90C11
url https://arxiv.org/abs/2604.03078