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Machine learning based simulation optimisation for urban routing problems
Christopher Bayliss
School of Mathematics & Physics
Centre for Operational Research & Logistics
Research output
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peer-review
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INIS
machine learning
100%
optimization
71%
travel
71%
solutions
42%
simulation
42%
algorithms
28%
routing
28%
budgets
28%
roads
28%
data
14%
learning
14%
prediction
14%
range
14%
environment
14%
demand
14%
neural networks
14%
reliability
14%
stochastic processes
14%
trains
14%
vehicles
14%
surveillance
14%
simulators
14%
tourism
14%
Computer Science
Machine Learning
85%
Optimization
71%
Simulation
42%
Vehicle Routing
28%
Learning Component
28%
Teams
28%
Machine Learning Algorithm
14%
Algorithms
14%
Real World
14%
Prediction Time
14%
Network Structure
14%
Candidate Solution
14%
Learning Parameter
14%
Combinatorial Problem
14%
Multiple Instance
14%
Networks
14%
User
14%
Iterations
14%