Optimal Preventive Maintenance Scheduling of Multi State System. A Comparative Study of Different Meta-heuristic Algorithms

Authors

  • Kamel BELKACEM Electrical and Industrial Systems Laboratory (LSEI), Faculty of Electrical Engineering University of Sciences and Technology HouariBoumediene (USTHB) Algiers, Algeria
  • Noureddine BALI Electrical and Industrial Systems Laboratory (LSEI), Faculty of Electrical Engineering University of Sciences and Technology HouariBoumediene (USTHB) Algiers, Algeria
  • Hilal LABDELAOUI Electrical and Industrial Systems Laboratory (LSEI), Faculty of Electrical Engineering University of Sciences and Technology HouariBoumediene (USTHB) Algiers, Algeria

DOI:

https://doi.org/10.51485/ajss.v9i2.218

Keywords:

preventive maintenance, multi-state system, meta-heuristic, optimization

Abstract

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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Published

2024-06-30

How to Cite

[1]
BELKACEM, K. , BALI, N. and LABDELAOUI, H. 2024. Optimal Preventive Maintenance Scheduling of Multi State System. A Comparative Study of Different Meta-heuristic Algorithms. Algerian Journal of Signals and Systems . 9, 2 (Jun. 2024), 114-120. DOI:https://doi.org/10.51485/ajss.v9i2.218.

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Articles