A crow search algorithm for aircraft maintenance check problem and continuous airworthiness maintenance program

Abstract

This research discusses the maintenance problem of a small commer­cial aircraft with propeller engine, typed ATR-72. Based on the main­­tenance records, the aircraft has average 294 routine activities that have to be monitored and done based on determined threshold interval. This research focuses on developing a meta­heuristic model to optimize the aircraft’s utility, called Crow Search Algorithm (CSA) to solve the Aircraft Maintenance Problem (AMP). The algorithm is developed and tested whether a younger meta­heuristic method, CSA, is able to give better performance compar­ed to the older methods, Particle Swarm Optimization (PSO) and other hybri­dized method PSO with Greedy Randomized Adaptive Search Optimization (PSO-GRASP). Several experiments are performed by using parameters: 1000 maximum iteration and 600 maximum computa­tion time by using four dataset combinations. The results show that CSA can give better performance than PSO but worse than PSO-GRASP.

Keywords

• aircraft maintenance
• crow search algorithm
• greedy randomized adaptive search
• maintenance scheduling
• particle swarm optimization