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