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Multi-haul quasi network flow model for vertical alignment optimization

University of British Columbia

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 quasi network flow (QNF) models. The numerical results show that, within 1% relative error, the proposed model is robust and solves more than 93% of test problems. Whereas, the CTG only solves about 82% of test problems and QNF fails to solve any problem within 1% relative error. Moreover, in terms of computational time, on average the MH-QNF model solves the problems approximately 8 times faster than the CTG model.

Text

2016-07-15

Attribution-NonCommercial-NoDerivs 2.5 Canada

http://hdl.handle.net/2429/56673

Interdisciplinary Studies

University of British Columbia

UBCO

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/