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

Arash Kaviani (), Russell G. Thompson (), Abbas Rajabifard () and Majid Sarvi ()
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Arash Kaviani: The University of Melbourne
Russell G. Thompson: The University of Melbourne
Abbas Rajabifard: The University of Melbourne
Majid Sarvi: The University of Melbourne

Transportation, 2020, vol. 47, issue 1, No 5, 109-143

Abstract: 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 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11116-017-9852-5

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