Riyanto, Maya Novita Putri (2020) Optimasi Feeder Vehicle Routing Problem Pada Distribusi Pengiriman Barang dengan Menggunakan Multiple Travelling Salesman Problem dan Algoritme Genetika. Sarjana thesis, Universitas Brawijaya.
Abstract
Peningkatan jumlah penduduk berbanding lurus dengan peningkatan permintaaan barang. Block selling merupakan konsep pengiriman barang dengan pembagian area berdasarkan jumlah armada di perusahaan, tetapi jika barang di armada motor habis maka harus mengambil barang ke armada mobil, masalah ini disebut dengan istilah Feeder Vehicle Routing Problem. Peneliti akan melakukan optimasi Feeder Vehicle Routing Problem (FVRP) pada distribusi pengiriman barang dengan menggunakan Multiple Travelling Salesman Problem (MTSP) dan Algoritme Genetika. Pada representasi kromosom Algoritme Genetika berdasarkan konsep MTSP dilakukan pembagian Cluster untuk memetakan rute kendaraan pengiriman barang, meliputi Toko yang dituju setiap armada, kondisi reload atau tidak reload, pemilihan Mobil untuk reload, posisi Mobil, dan interval posisi titik temu reload barang. Tahap reproduksi crossover menggunakan Partial Mapped Crossover dan Extended Intermediate Crossover, sedangkan reproduksi mutasi dengan metode Reciprocal Exchange Mutation serta Random Mutation. Perhitungan nilai jarak menggunakan Haverseine Formula, kemudian hitung nilai fitness dan diseleksi dengan Elitism. Hasil pengujian mendapatkan nilai fitness terbesar 1,35926 disertai ukuran populasi sebanyak 50, nilai Cr 0,5 dan Mr 0,6 pada generasi 100, selain itu konvergensi fitness terdapat pada sekitar nilai 1,25 hingga 1,3. Pengujian dengan ukuran populasi bernilai 50 atau lebih dari 50, serta generasi sebanyak 100, dan nilai Cr 0,5 serta Mr 0,5, menghasilkan nilai fitness 1,266594973.
English Abstract
The increase in population is directly proportional to the increase in demand for goods. Block selling is a concept of shipping goods by dividing the area based on the number of fleets in the company, but if the goods in the motor fleet run out then they have to take the goods to the fleet of cars, this problem is called the Feeder Vehicle Routing Problem. Researchers will optimize the Feeder Vehicle Routing Problem (FVRP) on the distribution of freight shipments using Multiple Traveling Salesman Problems (MTSP) and Genetic Algorithms. In the Genetic Algorithm chromosome representation based on the MTSP concept, Cluster division is carried out to map the route of goods delivery vehicles, including the Shop to which each fleet goes, the condition of reloading or not reloading, the selection of Cars to reload, the position of the Car, and the position intervals of the point of reloading of goods. The phase of crossover reproduction uses Partial Mapped Crossover and Extended Intermediate Crossover, while the reproduction of mutations using the Reciprocal Exchange Mutation and Random Mutation methods. Calculation of distance using the Haverseine Formula, then calculate the value of fitness and selected with Elitism. The test results get the greatest fitness value of 1,35926 with a population size of 50, Cr value of 0,5 and Mr 0,6 in generation 100, besides fitness convergence is found around the value of 1,25 to 1,3. Tests with a population size of 50 or more than 50, and generation
Other obstract
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| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FILKOM/2020/228/052003418 |
| Uncontrolled Keywords: | algoritme genetika, multiple travelling salesman problem, feeder vehicle routing problem, distribusi barang, genetic algorithm, multiple travelling salesman problem, feeder vehicle routing problem, distribution of goods |
| Subjects: | 000 Computer science, information and general works > 005 Computer programming, programs, data > 005.1 Programming > 005.106 85 Software engineering / Capability maturity model (Computer software) |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Budi Wahyono Wahyono |
| Date Deposited: | 05 Aug 2020 08:21 |
| Last Modified: | 11 Apr 2023 03:54 |
| URI: | http://repository.ub.ac.id/id/eprint/180983 |
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