Improved Genetic Algorithm for Minimizing Periodic Preventive Maintenance Costs in Series-Parallel Systems

2010 ◽  
pp. 91-101
Author(s):  
Chung-Ho Wang ◽  
Te-Wei Lin
Keyword(s):  
Genetic Algorithm ◽  
Preventive Maintenance ◽  
Parallel Systems ◽  
Improved Genetic Algorithm ◽  
Maintenance Costs ◽  
In Series ◽  
Periodic Preventive Maintenance

Preventive Maintenance Optimization and Comparison of Genetic Algorithm Models in a Series–Parallel Multi-State System

2019 ◽  
Vol 28 (2) ◽  
pp. 219-230 ◽  
Author(s):  
Imane Maatouk ◽  
Iman Jarkass ◽  
Eric Châtelet ◽  
Nazir Chebbo
Keyword(s):  
Genetic Algorithm ◽  
Preventive Maintenance ◽  
Optimization Problem ◽  
Parallel Systems ◽  
Optimization Models ◽  
Maintenance Optimization ◽  
Maintenance Period ◽  
Characteristic Parameters ◽  
Maintenance Schedule ◽  
The Cost

Abstract In this research, different optimization models are developed to solve the preventive maintenance (PM) optimization problem in a maintainable multi-state series–parallel system. The objective is to determine for each component in the system the maintenance period minimizing a cost function under the constraint of required availability and for a specified horizon of time. Four genetic models based on the cost associated with maintenance schedule and availability characteristic parameters are constructed and analyzed. They are genetic algorithm (GA), hybridization GA and local search (GA-LS), fuzzy logic controlled GA (FLC-GA), and hybridization FLC-GA and LS. The experiment analyzes and compares the efficiency between them. These experiments investigate the effect of the parameters of the GA on the structure of optimal PM schedules in multi-state multi-component series–parallel systems. Results show that the hybridization FLC-GA and LS outperform the other algorithms.

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