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A multi-road quasi network flow model for vertical alignment optimization of a road network Ayman, Khandoker Md
Abstract
The vertical alignment optimization problem for road design focuses on finding the optimum vertical alignment of a single road with a minimum cost considering earthwork and satisfying all safety and design constraints. We proposed a new model named the multi-road quasi network flow model (MR-QNF) for vertical alignment optimization of the entire road network instead of just a single road. We then presented four different methods: one-at-a-time, no-flow, with-flow and divide and conquer methods to solve the vertical alignments of a road network. Here, the one-at-a-time method uses the old model named quasi network flow model (QNF) and is considered as the base model for comparison. The other three methods use the new MR-QNF model to solve this problem. We evaluated the performances of these methods on two real-world road network examples: one small road network (total road length is around 6 km) and one comparatively extensive road network (total length is around 66 km). The numerical results show that in the case of a small road network, it is possible to lower the total cost by 7.2\% by using the with-flow method and a speedup of 20 was achieved when compare to the one-at-a-time method. However, in the case of an extensive road network, the computation time of the one-at-a-time method is significantly lower than the other two methods without any notable differences in their costs.
Item Metadata
| Title |
A multi-road quasi network flow model for vertical alignment optimization of a road network
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| Creator | |
| Supervisor | |
| Publisher |
University of British Columbia
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| Date Issued |
2021
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| Description |
The vertical alignment optimization problem for road design focuses on finding the optimum vertical alignment of a single road with a minimum cost considering earthwork and satisfying all safety and design constraints. We proposed a new model named the multi-road quasi network flow model (MR-QNF) for vertical alignment optimization of the entire road network instead of just a single road. We then presented four different methods: one-at-a-time, no-flow, with-flow and divide and conquer methods to solve the vertical alignments of a road network. Here, the one-at-a-time method uses the old model named quasi network flow model (QNF) and is considered as the base model for comparison. The other three methods use the new MR-QNF model to solve this problem. We evaluated the performances of these methods on two real-world road network examples: one small road network (total road length is around 6 km) and one comparatively extensive road network (total length is around 66 km). The numerical results show that in the case of a small road network, it is possible to lower the total cost by 7.2\% by using the with-flow method and a speedup of 20 was achieved when compare to the one-at-a-time method. However, in the case of an extensive road network, the computation time of the one-at-a-time method is significantly lower than the other two methods without any notable differences in their costs.
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| Genre | |
| Type | |
| Language |
eng
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| Date Available |
2022-04-30
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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| DOI |
10.14288/1.0400196
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| URI | |
| Degree (Theses) | |
| Program (Theses) | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
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| Graduation Date |
2021-09
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| Campus | |
| Scholarly Level |
Graduate
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International