Benjamin Lacroix
Iterated racing algorithm for simulation-optimisation of maintenance planning.
Abstract
The purpose of this paper is two fold. First, we present a set of benchmark problems for maintenance optimisation called VMELight. This model allows the user to define the number of components in the system to maintain and a number of customisable parameters such as the failure distribution of the components, the spare part stock level and every costs associated with the preventive and corrective maintenances, unavailability and spare parts. From this model, we create a benchmark of 175 optimisation problems across different dimensions. This benchmark allows us to test the idea of using an iterated racing algorithm called IRACE based on the Friedman statistical test, to reduce the number of simulations needed to compare solutions in the population.We assess different population size and truncation rate to show that those parameters can have a strong influence on the performance of the algorithm.
Citation
LACROIX, B., MCCALL, J. and LONCHAMPT, J. 2018. Iterated racing algorithm for simulation-optimisation of maintenance planning. In Proceedings of the 2018 IEEE congress on evolutionary computation (CEC 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8477843. Available from: https://doi.org/10.1109/CEC.2018.8477843
Conference Name | 2018 IEEE congress on evolutionary computation (CEC 2018) |
---|---|
Conference Location | Rio de Janeiro, Brazil |
Start Date | Jul 8, 2018 |
End Date | Jul 13, 2018 |
Acceptance Date | Mar 15, 2018 |
Online Publication Date | Jul 8, 2018 |
Publication Date | Oct 4, 2018 |
Deposit Date | Oct 18, 2018 |
Publicly Available Date | Oct 18, 2018 |
Publisher | IEEE Institute of Electrical and Electronics Engineers |
Article Number | 8477843 |
DOI | https://doi.org/10.1109/CEC.2018.8477843 |
Keywords | Maintenance optimisation; Racing; Statistical test |
Public URL | http://hdl.handle.net/10059/3180 |
Files
LACROIX 2018 Iterated racing algorithm
(2.8 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc/4.0/
You might also like
Ensemble of deep learning models with surrogate-based optimization for medical image segmentation.
(2022)
Conference Proceeding
Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem.
(2022)
Conference Proceeding
Towards explainable metaheuristics: PCA for trajectory mining in evolutionary algorithms.
(2021)
Conference Proceeding
Towards the landscape rotation as a perturbation strategy on the quadratic assignment problem.
(2021)
Conference Proceeding