Pengembangan Model Optimasi Penjadwalan Aircraft Inspection Check dan Continuous Airworthiness Maintenance Program pada Satu Unit Pesawat Terbang

Adianto, Asyraf Nur (2019) Pengembangan Model Optimasi Penjadwalan Aircraft Inspection Check dan Continuous Airworthiness Maintenance Program pada Satu Unit Pesawat Terbang. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian ini berfokus pada penyelesaian permasalahan aircraft maintenance dengan menggunakan dua metode metaheuristik, yaitu metode Particle Swarm Optimization dan Crow Search Algorithm. Kedua metode tersebut dihibridisasi dengan metode metaheuristik lain yaitu metode Greedy Randomized Adaptive Search Procedures. Permasalahan pada penelitian ini mempertimbangkan keberadaan dua aktivitas maintenance berbeda yang wajib dilakukan oleh setiap maskapai, diantaranya yaitu aktivitas inspeksi dan aktivitas Continuous Airworthiness Maintenance Program. Permasalahan ini memiliki sifat NP-Hard sehingga untuk penyelesaian yang cepat membutuhkan penggunaan metode metaheuristik. Eksperimen dilakukan sebanyak 16 kondisi yang dikembangkan dari 4 dataset yang dibangkitkan secara acak. Hasil menunjukkan bahwa PSO-GRASP mampu memberikan hasil yang jauh lebih baik dari seluruh percobaan jika dibandingkan dengan CSA-GRASP.
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This research focused on solving aircraft maintenance problem using two metaheuristic method, Particle Swarm Optimization and Crow Search Algorithm. Both of them have been hybridized with Greedy Randomized Adaptive Search Procedures. Aircraft maintenance problem in this research related to maintenance task scheduling consist of two different maintenance activity type, inspection and continuous airworthiness maintenance programs (CAMP). Purpose of this paper is to determine number of periods the aircraft need to be maintained and which inspection and Continuous Airworthiness Maintenance Program task needs to be done on each period. This problem NP-Hard nature solved using those metaheuristic methods to make sure the optimization process could be done quickly. Computational experiment being done using 16 condition and using 4 randomly generated dataset instance. Result of the computational experiment that using larger planning horizon lead to PSO-GRASP outperform CSA-GRASP.

Item Type:	Thesis (Masters)
Subjects:	T Technology > T Technology (General) > T57.6 Operations research--Mathematics. Goal programming T Technology > TS Manufactures > TS174 Maintainability (Engineering) . Reliability (Engineering)
Divisions:	Faculty of Industrial Technology > Industrial Engineering > 26101-(S2) Master Thesis
Depositing User:	Asyraf Nur Adianto
Date Deposited:	22 Jul 2026 03:50
Last Modified:	22 Jul 2026 03:50
URI:	http://repository.its.ac.id/id/eprint/68581

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