A crow search algorithm for aircraft maintenance check problem and continuous airworthiness maintenance program
DOI:
https://doi.org/10.30656/jsmi.v3i2.1794Keywords:
Aircraft Maintenance, Crow Search Algorithm, Greedy Randomized Adaptive Search, Maintenance Scheduling, Particle Swarm OptimizationAbstract
This research discusses the maintenance problem of a small commerÂcial aircraft with propeller engine, typed ATR-72. Based on the mainÂÂtenance 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 metaÂheuristic 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 metaÂheuristic method, CSA, is able to give better performance comparÂed to the older methods, Particle Swarm Optimization (PSO) and other hybriÂdized method PSO with Greedy Randomized Adaptive Search Optimization (PSO-GRASP). Several experiments are performed by using parameters: 1000 maximum iteration and 600 maximum computaÂtion time by using four dataset combinations. The results show that CSA can give better performance than PSO but worse than PSO-GRASP.
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