Bi-objective knapsack problem with conflicts

Abstract In this work we propose a bi-objective variant of the well-known 0/1 Knapsack Problem, that finds application in cases in which some item pairs may be seen as mutually conflicting. Previous variants considered in this scenario proposed to either avoid all conflicts, or to deal with them by considering the payment of appropriate penalty costs. We propose a different approach where the maximization of the profit and the minimization of the accepted conflicts are considered two different objective functions. We aim at identifying all Pareto-optimal solutions, so that a decision maker may choose a posteriori the optimal trade-off. We propose an exact resolution method based on the $$\epsilon $$ -constraint approach. Computational results on a wide set of instances show that our approach can be used in practice to identify and analyze their Pareto front.

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Publication Details

Journal
Annals of Operations Research
Published
2025-10-03
DOI
https://doi.org/10.1007/s10479-025-06792-5
Citations
1
Primary Topic
Optimization and Packing Problems
Type
article
Field-Weighted Citation Impact
1.24
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article

Bi-objective knapsack problem with conflicts

Andrea Raiconi, Donatella Granata
1 citations
Annals of Operations Research
Optimization and Packing Problems
1.24
article

Bi-objective knapsack problem with conflicts

Andrea Raiconi, Donatella Granata
article en
1 citations

Abstract

Abstract In this work we propose a bi-objective variant of the well-known 0/1 Knapsack Problem, that finds application in cases in which some item pairs may be seen as mutually conflicting. Previous variants considered in this scenario proposed to either avoid all conflicts, or to deal with them by considering the payment of appropriate penalty costs. We propose a different approach where the maximization of the profit and the minimization of the accepted conflicts are considered two different objective functions. We aim at identifying all Pareto-optimal solutions, so that a decision maker may choose a posteriori the optimal trade-off. We propose an exact resolution method based on the $$\epsilon $$ -constraint approach. Computational results on a wide set of instances show that our approach can be used in practice to identify and analyze their Pareto front.

Annals of Operations ResearchVol. 357(2-3)
University of Parma (IT), Istituto per le Applicazioni del Calcolo Mauro Picone (IT)
Openalex Percentile: Top 15%
Optimization and Packing Problems
1.24
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Bi-objective knapsack problem with conflicts — Andrea Raiconi, Donatella Granata · Annals of Operations Research (2025) | TGRS Research Map | TGRS