Journal article

Hybrid machine learning and optimisation method to solve a tri-level road network protection problem

Arash Kaviani, Russell G Thompson, Abbas Rajabifard, Majid Sarvi

IET INTELLIGENT TRANSPORT SYSTEMS | INST ENGINEERING TECHNOLOGY-IET | Published : 2018

Abstract

In this study, the authors employ machine learning to develop a new solution method for solving a tri-level network protection problem. In the upper-level, the planner aims to minimise the impact of the interdictor's attempt to disrupt a road network through protection activities. At the middle-level, however, the interdictor seeks to maximise the network's cost function, that is total travel time while the user equilibrium assignment models the road users behaviour at the lower-level. The proposed solution algorithm combines implicit enumeration with machine learning for faster performance. In so doing, four machine learning methods are evaluated among which the artificial neural network mo..

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Grants

Awarded by Australian Research Council's Linkage Project: 'Planning and Managing Transport Systems for Extreme Events Through Spatial Enablement'


Funding Acknowledgements

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.