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Developing Optimal Planning and Management Strategies for a Robust Highway System
Abstract
The report attempts to deliver a proof of concept that optimal planning and management strategies can be formulated through applying robust optimization methodology such that limited resources could be allocated more rationally, and reliability of a highway network improved more efficiently.
The report focuses on two applications: the network design problem under demand uncertainty, and fleet allocation for freeway services patrols. Their corresponding decision-makings are formulated as several optimization models. By solving these models robust optimal strategies can be obtained. Numerical examples and simulation tests are presented to demonstrate the validity and usefulness of the proposed models.
The report has proved that through applying robust optimization methodology, robust optimal improvement strategies can be obtained to improve substantially the capacity of a highway system against high-consequence scenarios incurred by fluctuations in travel demand or irregular incidents.
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