Authors: Budi Santosa; Maria Krisnawati; Ahmad Rusdiansyah
Addresses: Department of Industrial Engineering, Institut Teknologi Sepuluh November (ITS), 60111, Kampus ITS, Sukolilo, Surabaya, Indonesia ' Department of Industrial Engineering, Jenderal Soedirman University, 53371, Jalan Mayjend Sungkono Km. 5 Purbalingga, Indonesia ' Department of Industrial Engineering, Institut Teknologi Sepuluh November (ITS), 60111, Kampus ITS, Sukolilo, Surabaya, Indonesia
Abstract: This paper presents a comparison of metaheuristics algorithms for solving crew rostering problem in airline company. Many optimisation methods have been developed to improve both roster quality and computational time. This paper proposes simple iterative mutation (SIMA) method to solve airline crew rostering problem. The proposed method is originated from genetic algorithm. Unlike genetics algorithm which is commonly used, the proposed simple iterative method consists of only three steps including initialisation, selection, and mutation. The method is applied to the datasets from Indonesia airline company, Merpati Nusantara Airline (MNA). To evaluate the performance of the proposed method, the results are compared to those of cross entropy, differential evolution, column generation and MOSI (method used by the airline) in minimising number of assigned crews to cover all of scheduled flights. From the experiments, SIMA method produced better result in term of roster quality and computational time.
Keywords: airline crew rostering; genetic algorithm; roster quality; Indonesia.
International Journal of Metaheuristics, 2020 Vol.7 No.4, pp.307 - 329
Accepted: 11 Nov 2019
Published online: 26 Nov 2020 *