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  1. Research Outputs

New Exact Techniques Applied to a Class of Network Flow Formulations

Conference Paper
Publication Date:
2021
Short description:
New Exact Techniques Applied to a Class of Network Flow Formulations / De Lima, V. L.; Iori, M.; Miyazawa, F. K.. - 12707:(2021), pp. 178-192. ( 22nd International Conference on Integer Programming and Combinatorial Optimization, IPCO 2021 Chicago 2021) [10.1007/978-3-030-73879-2_13].
abstract:
We propose a number of solution techniques for general network flow formulations derived from Dantzig-Wolfe decompositions. We present an arc selection method to derive reduced network flow models that may potentially provide good feasible solutions. This method is explored as a variable selection rule for branching. With the aim of improving reduced-cost variable-fixing, we also propose a method to produce different dual solutions of network flow models and provide conditions that guarantee the correctness of the method. We embed the proposed techniques in an innovative branch-and-price method for network flow formulations, and test it on the cutting stock problem. In our computational experiments, 162 out of 237 open benchmark instances are solved to proven optimality within a reasonable computational time, consistently improving previous results in the literature.
Iris type:
Relazione in Atti di Convegno
Keywords:
Network flow models; Variable fixing; Variable selection
List of contributors:
De Lima, V. L.; Iori, M.; Miyazawa, F. K.
Authors of the University:
IORI MANUEL
Handle:
https://iris.unimore.it/handle/11380/1251649
Book title:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Published in:
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Journal
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Series
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