What is he best known for?
The fields of study he is best known for:
- Statistics
- Algorithm
- Mathematical optimization
His primary areas of investigation include Simulation, Robustness, Transport engineering, Scheduling and Energy consumption.
In the subject of general Simulation, his work in Headway is often linked to Track, Track circuit and Operation control, thereby combining diverse domains of study.
Rob M.P. Goverde regularly links together related areas like Operations research in his Transport engineering studies.
His Operations research research is multidisciplinary, relying on both Realizability, Linear system and Stability theory.
As part of one scientific family, Rob M.P. Goverde deals mainly with the area of Scheduling, narrowing it down to issues related to the Computation, and often Traffic congestion reconstruction with Kerner's three-phase theory, Traffic conditions and Linear programming.
Rob M.P. Goverde interconnects Copula and Bayesian network in the investigation of issues within Mathematical optimization.
His most cited work include:
- Railway Timetable Stability Analysis Using Max-plus System Theory (165 citations)
- Review of energy-efficient train control and timetabling (123 citations)
- A delay propagation algorithm for large-scale railway traffic networks (115 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Operations research, Transport engineering, Track, Mathematical optimization and Simulation.
His Operations research research incorporates elements of State, Contingency plan, Rail transportation, Scheduling and Traffic conditions.
The concepts of his Transport engineering study are interwoven with issues in Stability, Service and Robustness.
His work on Integer programming, Linear programming and Optimization problem as part of general Mathematical optimization research is frequently linked to Cycle time and Line, thereby connecting diverse disciplines of science.
His Headway study, which is part of a larger body of work in Simulation, is frequently linked to Dwell time, Running time and Statistical analysis, bridging the gap between disciplines.
His Real-time computing study combines topics from a wide range of disciplines, such as Algorithm and Linear system.
He most often published in these fields:
- Operations research (30.88%)
- Transport engineering (21.32%)
- Track (18.38%)
What were the highlights of his more recent work (between 2017-2021)?
- Operations research (30.88%)
- Mathematical optimization (16.91%)
- Service (9.56%)
In recent papers he was focusing on the following fields of study:
Rob M.P. Goverde mostly deals with Operations research, Mathematical optimization, Service, Trajectory optimization and Energy consumption.
His research in Operations research intersects with topics in Travel time, State and Integer programming.
Rob M.P. Goverde has researched Mathematical optimization in several fields, including Retiming, Subnetwork and Robustness.
Rob M.P. Goverde has included themes like Stochastic programming and Stochastic modelling in his Robustness study.
Rob M.P. Goverde combines subjects such as Braking distance, Reliability engineering, Reliability, Scheduling and Rule of thumb with his study of Service.
His Trajectory optimization study integrates concerns from other disciplines, such as Envelope and Parametric statistics.
Between 2017 and 2021, his most popular works were:
- Recent applications of big data analytics in railway transportation systems: A survey (84 citations)
- Multi-train trajectory optimization for energy-efficient timetabling (35 citations)
- Railway timetable rescheduling with flexible stopping and flexible short-turning during disruptions (26 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Algorithm
- Mathematical optimization
His primary areas of study are Mathematical optimization, Operations research, Robustness, Travel time and Capacity assessment.
His study in the fields of Trajectory optimization and Optimal control under the domain of Mathematical optimization overlaps with other disciplines such as Efficient energy use, Schedule and Energy consumption.
His work deals with themes such as Crew scheduling and Event scheduling, which intersect with Operations research.
His Robustness study integrates concerns from other disciplines, such as Rolling horizon, Stochastic programming, Stochastic modelling and Punctuality.
His Travel time study incorporates themes from Discrete event simulation and Unavailability.
His work in Capacity assessment incorporates the disciplines of Signalling, Distributed computing, Interlocking, Blocking and Network planning and design.
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