Optimal Preventive Maintenance Scheduling of Multi State System. A Comparative Study of Different Meta-heuristic Algorithms
DOI:
https://doi.org/10.51485/ajss.v9i2.218Keywords:
preventive maintenance, multi-state system, meta-heuristic, optimizationAbstract
This work presents a comparative study of different meta-heuristic algorithms which are commonly used in the literature, such as Genetic Algorithms, Particle Swarm Optimization, Artificial Bee Colony and Grey Wolf Optimizer. These algorithms are applied to solve a multi-state system maintenance optimization problem considering time and system availability constraints. The objective is to find the optimal inspection and maintenance intervals for each component of the system in order to minimize the preventive maintenance cost of overall the system. The performances of the algorithms are compared using different metrics, regarding the quality and stability of the results and the speed of convergence, in order to determine the most efficient algorithms.
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Copyright (c) 2024 Kamel BELKACEM, Noureddine BALI, Hilal LABDELAOUI
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.