Beatriz M. MĂ©ndez-HernĂĄndez, Jessica Coto Palacio, Yailen MartĂnez JimĂ©nez, Ann Nowé, Erick D. RodrĂguez Bazan
Scheduling problems appear on a regular basis in many real life situations, whenever it is necessary to allocate resources to perform tasks, optimizing one or more objective functions. Depending on the problem being solved, these tasks can take different forms, and the objectives can also vary. This research addresses scheduling in manufacturing environments, where the reports requested by the customers have to be scheduled in a set of machines with capacity constraints. Additionally, there is a set of limitations imposed by the company that must be taken into account when a feasible solution is built. To solve this problem, a general algorithm is proposed, which initially distributes the total capacity of the system among the existing resources, taking into account the capacity of each them, after that, each resource decides in which order it will process the reports assigned to it. The experimental study performed shows that the proposed approach allows to obtain feasible solutions for the report scheduling problem, improving the results obtained by other scheduling methods.
MĂ©ndez-HernĂĄndez, BM, Coto Palacio, J, MartĂnez JimĂ©nez, Y, NowĂ©, A & RodrĂguez Bazan, ED 2018, A reinforcement learning approach for the report scheduling process under multiple constraints. in YH Heredia, VM NĂșñez & JR Shulcloper (eds), 6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11047 LNCS, Springer Verlag, pp. 228-235, 6th International Workshop on Artificial Intelligence and Pattern Recognition, Havana, Cuba, 12/09/18. https://doi.org/10.1007/978-3-030-01132-1_26
MĂ©ndez-HernĂĄndez, B. M., Coto Palacio, J., MartĂnez JimĂ©nez, Y., NowĂ©, A., & RodrĂguez Bazan, E. D. (2018). A reinforcement learning approach for the report scheduling process under multiple constraints. In Y. H. Heredia, V. M. NĂșñez, & J. R. Shulcloper (Eds.), 6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018 (pp. 228-235). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11047 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-01132-1_26
@inproceedings{cc82c63d628e42dcb05f8a2832a86d77,
title = "A reinforcement learning approach for the report scheduling process under multiple constraints",
abstract = "Scheduling problems appear on a regular basis in many real life situations, whenever it is necessary to allocate resources to perform tasks, optimizing one or more objective functions. Depending on the problem being solved, these tasks can take different forms, and the objectives can also vary. This research addresses scheduling in manufacturing environments, where the reports requested by the customers have to be scheduled in a set of machines with capacity constraints. Additionally, there is a set of limitations imposed by the company that must be taken into account when a feasible solution is built. To solve this problem, a general algorithm is proposed, which initially distributes the total capacity of the system among the existing resources, taking into account the capacity of each them, after that, each resource decides in which order it will process the reports assigned to it. The experimental study performed shows that the proposed approach allows to obtain feasible solutions for the report scheduling problem, improving the results obtained by other scheduling methods.",
keywords = "Dispatching rules, Parallel machines, Reinforcement learning, Reports scheduling",
author = "M{\'e}ndez-Hern{\'a}ndez, {Beatriz M.} and {Coto Palacio}, Jessica and {Mart{\'i}nez Jim{\'e}nez}, Yailen and Ann Now{\'e} and {Rodr{\'i}guez Bazan}, {Erick D.}",
year = "2018",
month = jan,
day = "1",
doi = "10.1007/978-3-030-01132-1_26",
language = "English",
isbn = "9783030011314",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "228--235",
editor = "Heredia, {Yanio Hern{\'a}ndez} and N{\'u}{\~n}ez, {Vladimir Mili{\'a}n} and Shulcloper, {Jos{\'e} Ruiz}",
booktitle = "6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018",
address = "Germany",
note = "6th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2018 ; Conference date: 12-09-2018 Through 26-09-2018",
}