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arXiv · 1701.01768

Multi-Haul Quasi Network Flow Model for Vertical Alignment Optimization

Vahid Beiranvand·Warren Hare·Yves Lucet·Shahadat Hossain
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Abstract

The vertical alignment optimization problem for road design aims to generate a vertical alignment of a new road with a minimum cost, while satisfying safety and design constraints. We present a new model called multi-haul quasi network flow (MH-QNF) for vertical alignment optimization that improves the accuracy and reliability of previous mixed integer linear programming models. We evaluate the performance of the new model compared to two state-of-the-art models in the field: the complete transportation graph (CTG) and the quasi network flow (QNF) models. The numerical results show that, within a 1% relative error, the proposed model is robust and solves more than 93% of test problems compared to 82% for the CTG and none for the QNF. Moreover, the MH-QNF model solves the problems approximately 8 times faster than the CTG model.

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Vahid Beiranvand, Warren Hare, Yves Lucet, Shahadat Hossain. 2017-01-06. Multi-Haul Quasi Network Flow Model for Vertical Alignment Optimization. https://doi.org/10.1080/0305215x.2016.1271880

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