Pamungkas, Meidani Nuzul Tri (2022) Multi-Objective Vehicle Routing Problem with Time Window and Drones (MO-VRPTW-D) Menggunakan Algoritma Simulated Annealing dan Ant Colony Optimization untuk Last-Mile Delivery. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Drone adalah kendaraan udara tanpa awak yang saat ini sedang marak digunakan dalam bidang fotografi dan bidang lainnya. Dalam kondisi khusus, drone digunakan untuk kendaraan logistik di mana barang-barang harus diangkut oleh truk yang dilengkapi dengan drone karena bentuk lahannya atau bahkan karena lokasinya vertikal (seperti apartemen, hotel, dll) yang tentunya tidak dapat dijangkau oleh truk. Multi-Objective Vehicle Routing Problem with Time Window and Drones (MO-VRPTW-D), di mana tujuannya adalah meminimasi biaya dengan cara mencari rute yang optimal agar konsumsi energi truk, konsumsi energi drone, dan jumlah truk yang dibutuhkan minimal. Problem ini menjadi kompleks apabila jumlah destinasi yang dikunjungi banyak. Pendekatan metaheuristik diperlukan untuk menyelesaikan problem ini karena kompleksitas yang tinggi walaupun solusi yang dihasilkan belum tentu optimal global. Algoritma Simulated Annealing dan Ant Colony Optimization dipilih karena terbukti cukup efektif untuk menyelesaikan problem kombinatorial semacam penentuan rute. Inovasi ini dapat diadopsi oleh perusahaan jasa pengiriman pada masa mendatang karena pengiriman akan menjadi lebih efisien, cepat, dan mengurangi biaya secara signifikan. Eksperimen dilakukan dalam 24 skenario dengan jumlah pelanggan 25 – 200. Algoritma ACO mampu menghasilkan solusi lebih baik daripada Algoritma SA sebanyak 15 dari total 24 skenario.
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Drone is remote controlled aerial vehicle that is currently being widely used in photography and other fields. In special conditions, drones are used for logistics vehicles where goods must be transported by trucks equipped with drones because of the shape of the land or even because of its vertical location (such as apartments, hotels, etc.) Multi-Objective Vehicle Routing Problem with Time Window and Drones (MO-VRPTW-D), where the goal is to minimize costs by finding the optimal route so that truck energy consumption, drone energy consumption, and the number of trucks needed are minimal. This problem becomes complex if the number of destinations visited is large. A metaheuristic approach is needed to solve this problem because of its high complexity, although the resulting solution is not necessarily global optimal. The Simulated Annealing and Ant Colony Optimization Algorithm was chosen because it proved to be quite effective in solving combinatorial problems such as route determination. This innovation can be applied by shipping service companies in the future because shipping will be more efficient, faster, and reduce costs significantly. Experiments were carried out in 24 scenarios with the number of customers 25 – 200. The ACO Algorithm was able to produce a better solution than the SA Algorithm by 15 out of a total of 24 scenarios.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Ant Colony Optimization, Logistik, Metaheuristik, Multi-Objective Vehicle Routing Problem with Time Window and Drones, Simulated Annealing ============================================================ Ant Colony Optimization, Logistics, Metaheuristic, Multi-Objective Vehicle Routing Problem with Time Window and Drones, Simulated Annealing |
| Subjects: | T Technology > T Technology (General) > T57.74 Linear programming T Technology > T Technology (General) > T57.8 Nonlinear programming. Support vector machine. Wavelets. Hidden Markov models. T Technology > T Technology (General) > T57.84 Heuristic algorithms. |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26201-(S1) Undergraduate Thesis |
| Depositing User: | Meidani Nuzul Tri Pamungkas |
| Date Deposited: | 11 Feb 2022 20:41 |
| Last Modified: | 18 Oct 2024 02:55 |
| URI: | http://repository.its.ac.id/id/eprint/93815 |
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