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