OPTIMIZATION OF LOGISTICS DISTRIBUTION ROUTES USING SA AND GA WITH DIFFERENT VEHICLE CAPACITIES
Capacitated vehicle routing problem (CVRP) is a variation of vehicle routing problem (VRP) that has capacity on the vehicle used. The method used to solve this CVRP problem is the meta-heuristic method. The meta-heuristic method used includes Simulated Annealing (SA) and Genetic Algorithm (GA). B...
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id-itb.:473652020-04-09T12:29:00ZOPTIMIZATION OF LOGISTICS DISTRIBUTION ROUTES USING SA AND GA WITH DIFFERENT VEHICLE CAPACITIES Rino Pratama, Rizki Indonesia Theses VRP, CVRP, Optimization Routes, Simulated Annealing, Genetic Algorithm. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/47365 Capacitated vehicle routing problem (CVRP) is a variation of vehicle routing problem (VRP) that has capacity on the vehicle used. The method used to solve this CVRP problem is the meta-heuristic method. The meta-heuristic method used includes Simulated Annealing (SA) and Genetic Algorithm (GA). Based on this method, the best route optimization results in ten different cases. Then compare the results of the two methods used with the results of the Best Known Solution (BKS) data for the same case from the company. The results show that for the first, second and fourth cases, among others, 8 nodes with 3 vehicles, 10 nodes with 3 vehicles, and 14 nodes with 4 vehicles have the same results between the two methods used, but both methods have the best cost value. better than BKS data. While for the following cases, the SA method has a better cost value than the GA method, while the best cost value is better than the BKS data. text |
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Capacitated vehicle routing problem (CVRP) is a variation of vehicle routing
problem (VRP) that has capacity on the vehicle used. The method used to solve this
CVRP problem is the meta-heuristic method. The meta-heuristic method used
includes Simulated Annealing (SA) and Genetic Algorithm (GA). Based on this
method, the best route optimization results in ten different cases. Then compare the
results of the two methods used with the results of the Best Known Solution (BKS)
data for the same case from the company. The results show that for the first, second
and fourth cases, among others, 8 nodes with 3 vehicles, 10 nodes with 3 vehicles,
and 14 nodes with 4 vehicles have the same results between the two methods used,
but both methods have the best cost value. better than BKS data. While for the
following cases, the SA method has a better cost value than the GA method, while
the best cost value is better than the BKS data. |
format |
Theses |
author |
Rino Pratama, Rizki |
spellingShingle |
Rino Pratama, Rizki OPTIMIZATION OF LOGISTICS DISTRIBUTION ROUTES USING SA AND GA WITH DIFFERENT VEHICLE CAPACITIES |
author_facet |
Rino Pratama, Rizki |
author_sort |
Rino Pratama, Rizki |
title |
OPTIMIZATION OF LOGISTICS DISTRIBUTION ROUTES USING SA AND GA WITH DIFFERENT VEHICLE CAPACITIES |
title_short |
OPTIMIZATION OF LOGISTICS DISTRIBUTION ROUTES USING SA AND GA WITH DIFFERENT VEHICLE CAPACITIES |
title_full |
OPTIMIZATION OF LOGISTICS DISTRIBUTION ROUTES USING SA AND GA WITH DIFFERENT VEHICLE CAPACITIES |
title_fullStr |
OPTIMIZATION OF LOGISTICS DISTRIBUTION ROUTES USING SA AND GA WITH DIFFERENT VEHICLE CAPACITIES |
title_full_unstemmed |
OPTIMIZATION OF LOGISTICS DISTRIBUTION ROUTES USING SA AND GA WITH DIFFERENT VEHICLE CAPACITIES |
title_sort |
optimization of logistics distribution routes using sa and ga with different vehicle capacities |
url |
https://digilib.itb.ac.id/gdl/view/47365 |
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