We study a novel version of the capacitated facility location problem, which includes incompatibilities among customers. For this problem, we propose and compare on a fair common ground a portfolio of metaheuristic techniques developed independently from each other. We tested our techniques on a new dataset composed of instances of increasing size, varying from medium to very large ones. The outcome is that the technique based on data mining has been able to outperform the others in most instances, except for a few large cases, for which it is overcome by the simpler greedy one. In order to encourage future comparisons on this problem, we make the instances, solution validator and implementations of the metaheuristic techniques available to the community.
Metaheuristic techniques for the capacitated facility location problem with customer incompatibilities
Mario Francesco Pavone;
2023-01-01
Abstract
We study a novel version of the capacitated facility location problem, which includes incompatibilities among customers. For this problem, we propose and compare on a fair common ground a portfolio of metaheuristic techniques developed independently from each other. We tested our techniques on a new dataset composed of instances of increasing size, varying from medium to very large ones. The outcome is that the technique based on data mining has been able to outperform the others in most instances, except for a few large cases, for which it is overcome by the simpler greedy one. In order to encourage future comparisons on this problem, we make the instances, solution validator and implementations of the metaheuristic techniques available to the community.File | Dimensione | Formato | |
---|---|---|---|
pavone-soco2022.pdf
solo gestori archivio
Tipologia:
Versione Editoriale (PDF)
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
491.31 kB
Formato
Adobe PDF
|
491.31 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.