Benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery
The dataset for Multi Depot Dynamic Vehicle Routing Problem with Stochastic Road Capacity (MDDVRPSRC) is presented in this paper. The data consist of 10 independent designs of evolving road networks ranging from 14-49 nodes. Together with the road networks are the Damage file (DF) for each correspon...
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2022
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my.upm.eprints.1005212023-11-21T08:35:40Z http://psasir.upm.edu.my/id/eprint/100521/ Benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery Anuar, Wadi Khalid Lee, Lai Soon Pickl, Stefan The dataset for Multi Depot Dynamic Vehicle Routing Problem with Stochastic Road Capacity (MDDVRPSRC) is presented in this paper. The data consist of 10 independent designs of evolving road networks ranging from 14-49 nodes. Together with the road networks are the Damage file (DF) for each corresponding road network. The DF simulates the damage level of roads within the networks due to a disaster source, thus affecting travel time and road capacity. We applied this data to test our proposed algorithm and validate our proposed model. This dataset served as an addition to the Vehicle Routing Problem (VRP) datasets that specifically addressed the road capacity problem during a disaster from an epicentre and could be used for other applications that constitute chaotic events and compromised road networks. Elsevier 2022-04 Article PeerReviewed Anuar, Wadi Khalid and Lee, Lai Soon and Pickl, Stefan (2022) Benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery. Data in Brief, 41. art. no. 107901. pp. 1-11. ISSN 2352-3409 https://www.sciencedirect.com/science/article/pii/S2352340922001135 10.1016/j.dib.2022.107901 |
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The dataset for Multi Depot Dynamic Vehicle Routing Problem with Stochastic Road Capacity (MDDVRPSRC) is presented in this paper. The data consist of 10 independent designs of evolving road networks ranging from 14-49 nodes. Together with the road networks are the Damage file (DF) for each corresponding road network. The DF simulates the damage level of roads within the networks due to a disaster source, thus affecting travel time and road capacity. We applied this data to test our proposed algorithm and validate our proposed model. This dataset served as an addition to the Vehicle Routing Problem (VRP) datasets that specifically addressed the road capacity problem during a disaster from an epicentre and could be used for other applications that constitute chaotic events and compromised road networks. |
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Article |
author |
Anuar, Wadi Khalid Lee, Lai Soon Pickl, Stefan |
spellingShingle |
Anuar, Wadi Khalid Lee, Lai Soon Pickl, Stefan Benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery |
author_facet |
Anuar, Wadi Khalid Lee, Lai Soon Pickl, Stefan |
author_sort |
Anuar, Wadi Khalid |
title |
Benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery |
title_short |
Benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery |
title_full |
Benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery |
title_fullStr |
Benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery |
title_full_unstemmed |
Benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery |
title_sort |
benchmark dataset for multi depot vehicle routing problem with road capacity and damage road consideration for humanitarian operation in critical supply delivery |
publisher |
Elsevier |
publishDate |
2022 |
url |
http://psasir.upm.edu.my/id/eprint/100521/ https://www.sciencedirect.com/science/article/pii/S2352340922001135 |
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1783879923016925184 |
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13.18916 |