Widyadiyanti, Ditya Kalika (2023) Penentuan Rute Distribusi Kendaraan Motor Listrik Berpendingin Untuk Meminimasi Biaya Distribusi Menggunakan Metode Ant Colony Optimization Dan Tabu Search. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Electric Vehicle Routing Problem with Time Windows (E-VRPTW) merupakan salah satu permasalahan yang dikembangkan dari permasalahan operasional distribusi kendaraan listrik seperti adanya keterbatasan kapasitas energi baterai dan kesulitan dalam menemukan stasiun pengisian daya untuk kendaraan listrik. Dalam rangka mengoptimalkan rute distribusi dari sebuah perusahaan logistik yang menggunakan kendaraan motor berpendingin berbasis bahan bakar listrik atau electric vehicle (EV) untuk mendistribusikan produk perishable (tidak tahan lama) perlu dipertimbangkan temperatur sebagai atribut dalam menjaga kualitas produk
serta hubungan temperatur tersebut kepada konsumsi energi baterai kendaraan. Pada penelitian ini dilakukan pengembangan algoritma Electric Vehicle Routing Problem
(EVRPTW) dengan tujuan meminimumkan total biaya distribusi yang terdiri dari biaya pengadaan kendaraan, transportasi, persediaan (loss quality), energi, dan penalti karena keterlambatan. Dalam tugas akhir ini EVRPTW diselesaikan menggunakan Ant Colony Optimization (ACO) yang berdasarkan pada observasi perilaku koloni semut dalam menentukan jalur terpendek untuk mencari lokasi makanan yang kemudian disempurnakan menggunakan Tabu Search (TS) dalam pengambilan keputusan. Penyelesaian EVRPTW menggunakan algoritma ACOTS ini diujicobakan pada data set Solomon Problem, yang
merupakan dataset standar permasalahan internasional VRPTW. Pada penelitian ini, dipaparkan perbandingan biaya distribusi pada kendaraan listrik dan kendaraan konvensional
serta perbandingan biaya distribusi pada kendaraan listrik dengan temperatur cold storage yang berbeda-beda.
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The Electric Vehicle Routing Problem with Time Windows (EVRPTW) is one of the problems developed from the distribution operation problems of electric vehicles, such as limited battery energy capacity and difficulty finding charging stations for electric vehicles (EV). In order to optimize the distribution routes of a logistics company that uses electric refrigerated motor vehicles to distribute perishable products, it is necessary to consider temperature as an attribute in maintaining product quality and the relationship between temperature and energy consumption of the vehicle battery. In this research, the development of the Electric Vehicle Routing Problem (EVRPTW) algorithm was carried out with the aim of minimizing the total distribution costs, consisting of the costs of vehicle procurement, transportation, inventory (loss quality), energy, and penalties due to delays. In this final project, EVRPTW is solved using Ant Colony Optimization (ACO), which
is based on observation of the behavior of ant colonies in determining the shortest path to food locations, which then refined using Tabu Search (TS) in decision making. The EVRPTW solution using the ACOTS algorithm was tested on the Solomon Problem data set, which is an international standard for VRPTW problems. In this study, a comparison of distribution costs for electric vehicles and conventional vehicles is presented. In addition, there is an explanation of the comparison of distribution costs for electric vehicles with different cold storage temperatures.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Produk perishable, EVRPTW, Ant Colony Optimization, Tabu Search, Kendaraan listrik, perishable product, EVRPTW, Ant Colony Optimization, Tabu Search, Electric Vehicle |
| Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL220 Electric vehicles and their batteries, etc. |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26201-(S1) Undergraduate Thesis |
| Depositing User: | Ditya Kalika Widyadiyanti |
| Date Deposited: | 05 Aug 2023 02:38 |
| Last Modified: | 05 Aug 2023 02:38 |
| URI: | http://repository.its.ac.id/id/eprint/101423 |
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