GeneRa: A Benchmarks Generator for RadiotherapyTreatment Scheduling Problems

Juan-Pablo Cares 1 Maria Cristina Riff 1 Bertrand Neveu 2, 3, 4
1 Departamento de Informatica [Valparaíso, Chile]
2 ENPC - École des Ponts ParisTech
3 IMAGINE [Marne-la-Vallée]
LIGM - Laboratoire d'Informatique Gaspard-Monge, CSTB - Centre Scientifique et Technique du Bâtiment, ENPC - École des Ponts ParisTech
4 LIGM - Laboratoire d'Informatique Gaspard-Monge
Abstract : The radiotherapy scheduling problems are hard constrained probllems that involve many resources including doctors, patients and machines.These problems are different according to the country, and can even varyamong institutions in the same country. Due to the lack of standard bench-marks, the algorithms proposed in the literature are very specific ones and they are not easily comparable or adaptable. We describe the radiotherapy schedul-ing problem in different countries in order to identify common components. Our goal in this paper is to provide a configurable benchmark generator for this problem able to take into account the specificities inherent to each country and institution. The benchmark generator is available online.
Type de document :
Communication dans un congrès
Learning and Intelligent OptimizatioN Conference LION 8, Feb 2014, Gainesville, United States. Springer, LNCS 8426, pp.353-361, 2014, Learning and Intelligent Optimization
Liste complète des métadonnées
https://hal-enpc.archives-ouvertes.fr/hal-01096097
Contributeur : Bertrand Neveu <>
Soumis le : mardi 16 décembre 2014 - 17:28:04
Dernière modification le : jeudi 5 juillet 2018 - 14:29:15

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  • HAL Id : hal-01096097, version 1

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ENPC | IMAGINE | LIGM_A3SI | LIGM | PARISTECH | UPEC-UPEM | ESIEE-PARIS

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Juan-Pablo Cares, Maria Cristina Riff, Bertrand Neveu. GeneRa: A Benchmarks Generator for RadiotherapyTreatment Scheduling Problems. Learning and Intelligent OptimizatioN Conference LION 8, Feb 2014, Gainesville, United States. Springer, LNCS 8426, pp.353-361, 2014, Learning and Intelligent Optimization. 〈hal-01096097〉

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