Anindya Maheswari, - (2024) PENYELESAIAN STOCHASTIC VEHICLE ROUTING PROBLEM BERBASIS SKENARIO DENGAN MENGGUNAKAN ALGORITMA SIMULATED ANNEALING. S1 thesis, Universitas Pendidikan Indonesia.
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Abstract
Penelitian ini membahas Stochastic Vehicle Routing Problem (SVRP), yaitu masalah penentuan rute pendistribusian sejumlah barang oleh kendaraan dari suatu depot ke sejumlah pelanggan lalu kembali ke depot. Permintaan pelanggan bersifat stochastic atau tidak pasti. Tujuan penyelesaian SVRP adalah untuk meminimalkan ekspektasi total jarak dengan mempertimbangkan batasan kapasitas kendaraan. Penelitian ini menyelesaikan SVRP berbasis skenario, di mana sejumlah skenario dibangkitkan, lalu menyelesaikan VRP untuk setiap skenario menggunakan Algoritma Simulated Annealing (SA). Solusi awal dibentuk secara random dengan tetap memperhatikan kendala batasan kapasitas kendaraan. Selanjutnya, fungsi objektif dari solusi awal dihitung, dan solusi baru dibangkitkan dengan metode Exchange, Insertion, atau Reversion. Jika solusi baru memiliki nilai fungsi objektif yang lebih baik, maka solusi baru akan diterima sebagai solusi sementara. Sebaliknya, solusi baru yang tidak lebih baik masih dapat diterima dengan suatu probabilitas tertentu. Pada setiap iterasi suhu akan diturunkan sampai memperoleh solusi optimal. Hasil implementasi SVRP pada penentuan rute pengangkutan sampah di Kota Nis menunjukkan bahwa Algoritma SA dapat menghasilkan rute kendaraan yang optimal dengan total jarak yang minimum. This research studies Stochastic Vehicle Routing Problem (SVRP), a problem to determine distribution routes for a number of vehicles from a depot to a number of customers and finish to the depot. The demand of customers is stochastic or uncertainty. SVRP is solved to minimize the total expected distance by satisfying vehicle capacity constraints. Using scenario-based approach, SVRP is solve by generating a number of scenarios, then on each scenario, we solve Vehicle Routing Problem using Simulated Annealing Algorithm. The initial solution is generated randomly while still taking into account vehicle capacity constraints. Next, the objective function of the initial solution is calculated, and a new solution is generated using the Exchange, Insertion, or Reversion method. If the new solution has a better objective function value, then the new solution will be accepted as a temporary solution. On the other hand, a new solution with greater objective value can still be accepted with a certain probability. In each iteration of Simulated Annealing, the temperature will be reduced until the optimal solution is obtained. The implementation results of SVRP in solving waste transportation routes in Nis City show that the Simulated Annealing Algorithm can produce optimal vehicle routes with a minimum total distance.
| Item Type: | Thesis (S1) |
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| Additional Information: | ID SINTA Dosen Pembimbing: Khusnul Novianingsih: 258640 Cece Kustiawan: 6674760 |
| Uncontrolled Keywords: | Stochastic Vehicle Routing Problem, Simulated Annealing, Permintaan Stochastic, Rute Kendaraan. Stochastic Vehicle Routing Problem, Simulated Annealing, Stochastic Demand, Vehicle Routing. |
| Subjects: | H Social Sciences > HE Transportation and Communications L Education > L Education (General) Q Science > QA Mathematics |
| Divisions: | Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Jurusan Pendidikan Matematika > Program Studi Matematika (non kependidikan) |
| Depositing User: | Anindya Maheswari |
| Date Deposited: | 07 Sep 2024 11:49 |
| Last Modified: | 07 Sep 2024 11:49 |
| URI: | http://repository.upi.edu/id/eprint/122913 |
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