Ulum, Moh. Yasya Bahrul (2017) Optimasi Vehicle Routing Problem dengan Packing Constraints Menggunakan Metode Algoritma Genetika. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Vehicle Routing Problem adalah suatu permasalahan dalam pengiriman barang dari depot ke beberapa outlet atau pelanggan menggunakan beberapa kendaraan yang memiliki kapasitas terbatas dengan tujuan meminimalkan biaya pengiriman. Adanya packing constraints dikarenakan pada umumnya kendaraan yang digunakan dalam pengiriman barang mempunyai kontainer berbentuk balok. Sehingga diperlukan cara-cara penyusunan agar kendaraan dapat memuat semua barang, tidak merusak barang dan memudahkan dalam mengeluarkan barang Dalam tugas akhir ini akan dikembangkan model dan algoritma untuk menyelesaikan vehicle routing problem with packing contraints dengan metode metaheuristik yaitu algoritma genetika dengan tujuan meminimalkan total jarak tempuh pengiriman. Selain itu gabungan algoritma genetika dan algoritma bottom-left fill digunakan untuk untuk melakukan proses packing agar didapat proses packing yang optimal. Algoritma genetika mengeluarkan hasil 0,08% lebih buruk dari ant colony optimization dan 2,93% lebih baik dari tabu search. Selain itu metode algoritma genetika juga berhasil diterapkan pada suatu perusahaan retail pada jaringan jalan kota Surabaya.
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Vehicle Routing Problem is a problem in delivering item from depot to all customers using several vehicles whose have limited capacity with purpose minimizing transportation cost. The packing constraints exist because the vehicles usually used in delivering item have a rectangular-box shaped container. The items itself also commonly have a shape of rectangular-box. Therefore, it needs a way to pack or load so that containers could load all of the items, not damage the items and make it easy to unload the items. The aim of this final project is developing a model and method as approach solution of vehicle routing problem with packing constraints using genetic algorithm to minimize the transportation mileage. In addition, a hybrid genetic algorithm and bottom-left fill algorithm also take place to solve the packing proses. This algorithm deliver average solution 0.08% worse than ant colony optimization but has 2.93% better than tabu search.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Routing, Optimization, Genetic Algortihm, Packing, Bottom-Left Fill |
| Subjects: | Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105.546 Computer algorithms |
| Divisions: | Faculty of Industrial Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Moh Yasya Bahrul Ulum |
| Date Deposited: | 18 Oct 2017 05:45 |
| Last Modified: | 06 Mar 2019 02:51 |
| URI: | http://repository.its.ac.id/id/eprint/47449 |
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