Perbandingan algoritma metaheuristic particle swarm optimization (PSO), tabu search dan simulated annealing (SA) untuk penyelesaian vehicle routing problem with time windows (VRPTW) = Comparison metaheuristic algorithm particle swarm optimization (PSO), tabu search and simulated annealing (SA) to solve vehicle routing problem with time windows (VRPTW)
| Main Author: | Herry Kartika Gandhi, author |
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| Format: | Masters Bachelors |
| Terbitan: |
, 2013
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| Subjects: |
Daftar Isi:
- <b>ABSTRAK</b><br> Vehicle Routing Problem with Time Windows menjadi suatu permasalahan bagi perusahaan saat ini dimana biaya logistik yang semakin tinggi. Penentuan rute yang tepat untuk distribusi barang sangat dibutuhkan untuk menekan biaya bahan bakar kendaraan. Penyelesaian VRPTW ini menggunakan algoritma metaheuristic: Tabu Search, Particle Swarm Optimization dan Simulated Annealing. Penelitian ini membandingkan karakter dari ketiga algoritma tersebut. Dimana hasil tabu search memberikan nilai yang mayoritas optimal dibandingkan ketiganya. Tetapi untuk iterasi pendek, PSO memberikan nilai yang cepat menuju optimal. <hr> <b>ABSTRACT</b><br> Vehicle Routing Problem with Time Windows become main problem to company when dealing with distribution cost that comes bigger. Determining best routing to distribute goods or service can help reduce distribution cost. This research using metaheuristic algorithm: Tabu Search, Particle Swarm Optimization dan Simulated Annealing to solve VRPTW. This research benchmark that three algorithm. The conclusion is tabu search bring best solution for long iteration. But for short iteration, PSO bring better solution.