To maintain their capacity,transportation infrastructures are in need of regular maintenance and rehabilitation.The major challenge facing transportation engineers is the network-level policies to maintain the deteriorating roads at an acceptable level of serviceability.In this work,a quantitative transportation network efficiency measure is presented and then how to determine optimally network-level road maintenance policy depending on the road importance to the network performance has been demonstrated.The examples show that the different roads should be set different maintenance time points in terms of the retention capacities of the roads,because the different roads play different roles in network and have different important degrees to the network performance.This network-level road maintenance optimization method could not only save lots of infrastructure investments,but also ensure the service level of the existing transportation system.
An optimization model and its solution algorithm for alternate traffic restriction(ATR) schemes were introduced in terms of both the restriction districts and the proportion of restricted automobiles. A bi-level programming model was proposed to model the ATR scheme optimization problem by aiming at consumer surplus maximization and overload flow minimization at the upper-level model. At the lower-level model, elastic demand, mode choice and multi-class user equilibrium assignment were synthetically optimized. A genetic algorithm involving prolonging codes was constructed, demonstrating high computing efficiency in that it dynamically includes newly-appearing overload links in the codes so as to reduce the subsequent searching range. Moreover,practical processing approaches were suggested, which may improve the operability of the model-based solutions.
