Solving the Problem of Aircraft Maintenance Using Particle Swarm Optimization

This chapter explores the application of Particle Swarm Optimization (PSO) to enhance aircraft maintenance strategies. The study focuses on minimizing maintenance costs, including components, preparation, downtime, and replacement, while adhering to technical constraints. It presents two objective functions to compare the impact of replacement costs on maintenance decisions. The PSO algorithm is detailed, including its steps and parameters, and adapted to solve the maintenance planning problem. Simulation results highlight the effectiveness of the approach, demonstrating a 21% reduction in total cost and improved system availability. The study also discusses the challenges of high replacement costs in aircraft maintenance and suggests future research directions, such as exploring alternative metaheuristic approaches and validating findings with other optimization algorithms.