On Solving the Maximum Flow Problem with Conflict Constraints

The Maximum Flow Problem with Conflict Constraints is a generalization that adds conflict constraints to a classical optimization problem on networks used to model several real-world applications. In the last few years several approaches, both heuristic and exact, have been proposed to attack the problem.In this paper we consider a mixed integer linear program and solve it with an open-source solver. Computational results on the benchmark instances commonly used in the literature of the problem are reported. All the 160 instances benchmark instances normally used in the literature are solved to optimality for the first time, with 28 instances closed for the first time. Moreover, in the process, 6 improvements to the best-known heuristic solutions are also found.

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Publication Details

Published
2025-09-08
DOI
https://doi.org/10.1109/ieacon64690.2025.11254654
Citations
1
Primary Topic
Vehicle Routing Optimization Methods
Type
article
Field-Weighted Citation Impact
1.24
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article

On Solving the Maximum Flow Problem with Conflict Constraints

Roberto Montemanni, Derek H. Smith
1 citations
Vehicle Routing Optimization Methods
1.24
article

On Solving the Maximum Flow Problem with Conflict Constraints

Roberto Montemanni, Derek H. Smith
article en
1 citations

Abstract

The Maximum Flow Problem with Conflict Constraints is a generalization that adds conflict constraints to a classical optimization problem on networks used to model several real-world applications. In the last few years several approaches, both heuristic and exact, have been proposed to attack the problem.In this paper we consider a mixed integer linear program and solve it with an open-source solver. Computational results on the benchmark instances commonly used in the literature of the problem are reported. All the 160 instances benchmark instances normally used in the literature are solved to optimality for the first time, with 28 instances closed for the first time. Moreover, in the process, 6 improvements to the best-known heuristic solutions are also found.

University of Modena and Reggio Emilia (IT), University of South Wales (GB)
Openalex Percentile: Top 13%
Vehicle Routing Optimization Methods
1.24
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