Advances in Production Engineering & Management
Volume 16 | Number 3 | September 2021 | pp 372–384
https://doi.org/10.14743/apem2021.3.407
A multi-objective selective maintenance optimization method for series-parallel systems using NSGA-III and NSGA-II evolutionary algorithms
Xu, E.B.; Yang, M.S.; Li, Y.; Gao, X.Q.; Wang, Z.Y.; Ren, L.J.
ABSTRACT AND REFERENCES (PDF) |
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A B S T R A C T
Aiming at the problem that the downtime is simply assumed to be constant and the limited resources are not considered in the current selective maintenance of the series-parallel system, a three-objective selective maintenance model for the series-parallel system is established to minimize the maintenance cost, maximize the probability of completing the next task and minimize the downtime. The maintenance decision-making model and personnel allocation model are combined to make decisions on the optimal length of each equipment’s rest period, the equipment to be maintained during the rest period and the maintenance level. For the multi-objective model established, the NSGA-III algorithm is designed to solve the model. Comparing with the NSGA-II algorithm that only considers the first two objectives, it is verified that the designed multi-objective model can effectively reduce the downtime of the system.
A R T I C L E I N F O
Keywords • Maintenance; Series-parallel system; Maintenance decision model; Multi-objective optimization; Selective maintenance; Evolutionary algorithms; Non-dominated sorting genetic algorithm; NSGA-II; NSGA-III
Corresponding author • Xu, E.B.
Article history • Received 1 July 2021, Revised 22 October 2021, Accepted 25 October 2021
Published on-line • 31 October 2021
E X P O R T C I T A T I O N
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