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A model for multi-class road network recovery scheduling of regional road networks

  • Arash Kaviani
  • Russell G. Thompson
  • Abbas Rajabifard
  • Majid Sarvi
Article

Abstract

In this paper, an optimisation model for recovery planning of road networks is presented in which both social and economic resilience is aimed to be achieved. The model is formulated as a bi-level multi-objective discrete network design problem which forms a non-convex mixed integer non-linear problem. Solved by a Branch and Bound method, the solution algorithm employs an outer approximation method to estimate the lower bound of each node in the Branch and Bound search tree. The solution algorithm exploits a unique approach for lower-bound computation dealing with a disrupted multi-class network that may not be able to satisfy the demand between all OD pairs due to damaged links. The model is assessed by applying it on the Sioux Falls network. It is also illustrated how the Pareto-optimal solutions achieved by the multi-objective optimisation can vary depending on the emphasis placed on different classes of vehicles.

Keywords

Transportation resilience Road network recovery Bi-level optimisation Discrete network design problem 

Notes

Acknowledgements

This paper is part of an ongoing research project on optimising diversion costs during road network recovery. This research is being conducted in the Centre for Disaster Management and Public Safety (CDMPS) at the Department of Infrastructure Engineering at The University of Melbourne. The authors acknowledge the kind support from the Australian Research Council’s Linkage Project, “Planning and Managing Transport Systems for Extreme Events Through Spatial Enablement” (LP140100369), VicRoads, and The Shire of Mornington Peninsula for providing us with invaluable resources.

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Authors’ contribution

Arash Kaviani: Ideation, Literature Review, Study Design, Problem Formulation, Mathematical Programming, Data Generation, Data Analysis, Manuscript Writing and Editing. Russell G. Thompson: Literature Review, Study Design, Problem Formulation, Data Analysis, Manuscript Writing and Editing. Abbas Rajabifard: Study Design, Manuscript Editing. Majid Sarvi: Study Design, Manuscript Editing.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Infrastructure Engineering, Centre for Disaster Management and Public SafetyThe University of MelbourneParkvilleAustralia

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