Optimalisasi Pemilihan Rute Penerbangan Kargo Udara Menggunakan Algoritma Artificial Bee Colony (ABC) dan Algoritma Artificial Bee Colony Based on Elite Strategy and Dimension Learning

Hafizh, Farhan (2022) Optimalisasi Pemilihan Rute Penerbangan Kargo Udara Menggunakan Algoritma Artificial Bee Colony (ABC) dan Algoritma Artificial Bee Colony Based on Elite Strategy and Dimension Learning. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pesawat udara merupakan transportasi utama untuk pengiriman barang yang bernilai tinggi maupun sensitif terhadap waktu. Penentuan rute pengiriman kargo udara yang didasarkan pada jaringan yang terhubung oleh masing-masing bandara dapat direncanakan dengan tujuan meminimumkan biaya yang terkait dengan biaya pengiriman, biaya transshipment, dan biaya operasional di bandara sehingga rute pengiriman yang terpilih memiliki biaya paling minimum. Dengan simulasi numerik terhadap total 6 bandara di Indonesia, model pemrograman linier bilangan bulat campuran dari pemilihan rute penerbangan kargo udara diselesaikan dengan perangkat lunak MATLAB menggunakan fungsi cplexmilp dari CPLEX. Selanjutnya model diselesaikan menggunakan metode metaheuristik dengan algoritma Artificial Bee Colony (ABC) dan Artificial Bee Colony Based on Elite Strategy and Dimension Learning (ABC-ESDL). Hasil simulasi numerik menunjukkan bahwa nilai objektif yang diperoleh menggunakan cplexmilp lebih minimum dibandingkan dengan algoritma ABC dan ABC-ESDL; dengan persentase masing-masing 10.41% dan 3.23% lebih besar daripada cplexmilp. Begitu pula dengan nilai objektif yang diperoleh menggunakan algoritma ABC-ESDL lebih minimum dibandingkan dengan algoritma ABC dengan persentase 6.96%. Hal ini menunjukkan bahwa dalam kasus meminimumkan biaya pengiriman kargo udara, performa algoritma ABC-ESDL lebih baik dibandingkan algoritma ABC. =================================================================================================== Airplanes are the main transportation mode for both high-value and time-sensitive goods delivery. Flight route selection of air cargo delivery based on the network connected by each airport can be planned with the aim of minimizing costs associated with shipping costs, transshipment costs, and operational costs at the airport so that the selected flight route has the minimum cost. By numerical simulation on a total of 6 airports in Indonesia, the mixed integer linear programming model of air cargo flight route selection was completed by MATLAB software using the cplexmilp function from CPLEX. Furthermore, the model was completed using a metaheuristic method with the Artificial Bee Colony (ABC) and Artificial Bee Colony Based on Elite Strategy and Dimension Learning (ABC-ESDL) algorithms. The results of numerical simulation show that the objective value obtained using cplexmilp is lower than the ABC and ABC-ESDL algorithms; with a percentage of 10.41% and 3.23%, respectively, greater than cplexmilp. Likewise, the objective value obtained using the ABC-ESDL algorithm is lower than the ABC algorithm with a percentage of 6.96%. This shows that in the case of minimizing air cargo shipping costs, the ABC-ESDL algorithm performances is better than the ABC algorithm.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Kargo Udara, Pemilihan Rute Penerbangan, Pemrograman Linier Bilangan Bulat Campuran, Artificial Bee Colony ======================================================================================================================== Air Cargo Transportation, Flight Route Selection, Mixed Integer Linear Programming, Artificial Bee Colony.
Subjects: H Social Sciences > HE Transportation and Communications > HE336.R68 Route choice
H Social Sciences > HE Transportation and Communications > HE9787.5 Airplanes--Ground handling
Q Science > QA Mathematics > QA336 Artificial Intelligence
Q Science > QA Mathematics > QA402.6 Transportation problems (Programming)
Q Science > QA Mathematics > QA9.58 Algorithms
Divisions: Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User: Farhan Hafizh
Date Deposited: 09 Feb 2022 03:51
Last Modified: 09 Feb 2022 03:51
URI: https://repository.its.ac.id/id/eprint/93160

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