Multi-haul quasi network flow model for vertical alignment optimization

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. A new model called multi-haul quasi network flow (MH-QNF) for vertical alignment optimization is presented with the goal of improving the accuracy and reliability of previous mixed integer linear programming models. The performance of the new model is compared with 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 eight times faster than the CTG model.