Integrating Predictive and Optimization Model for Intelligent Schedule Management based on Real Time ETA Information: A Concept of Machine Learning and Exact Solution in Petrochemical Loading Facility

This study addresses the truck rescheduling problem as the consequence of uncertain arrival time. It proposes an integrated system of predictive model powered by machine learning algorithm and exact optimization model such that it is distinct from most existing literatures in this domain. The uncertainty of truck arrival time is captured as...

Automated offline detection of disruptions using smart card data: A case study of the metro network of Washington DC

Service reliability is one of the most important performance measures to public transport users. Detecting disruptions helps to measure service reliability, which can be used by public transport operators to improve this reliability. In this thesis, a methodology is described to automatically detect disruptions offline, using smart card data....