What is he best known for?
The fields of study he is best known for:
- Statistics
- Mathematical optimization
- Information technology
His primary scientific interests are in Mathematical optimization, Traffic flow, Flow network, Simulation and Cell Transmission Model.
His Mathematical optimization research is multidisciplinary, relying on both Function and Computer simulation.
In his study, Ideal and Queueing theory is inextricably linked to Queue, which falls within the broad field of Traffic flow.
He combines subjects such as Network planning and design, Network performance, Reliability engineering, Risk aversion and Operations research with his study of Flow network.
His Simulation research incorporates elements of Scheduling and Traffic congestion.
The concepts of his Cell Transmission Model study are interwoven with issues in Traffic generation model, Newell's car-following model and Queue management system.
His most cited work include:
- Capacity reliability of a road network: an assessment methodology and numerical results (441 citations)
- Degradable transport network: Travel time budget of travelers with heterogeneous risk aversion (334 citations)
- NETWORK WITH DEGRADABLE LINKS: CAPACITY ANALYSIS AND DESIGN (301 citations)
What are the main themes of his work throughout his whole career to date?
Hong Kam Lo focuses on Transport engineering, Mathematical optimization, Operations research, Traffic flow and Network planning and design.
His Transport engineering research includes elements of Urban planning, Service and Flow network.
Hong Kam Lo has researched Mathematical optimization in several fields, including Queue, Simulation and Traffic congestion.
Queue is closely attributed to Queueing theory in his work.
He interconnects Travel time and Reliability in the investigation of issues within Operations research.
His research on Traffic flow focuses in particular on Cell Transmission Model.
He most often published in these fields:
- Transport engineering (30.08%)
- Mathematical optimization (19.80%)
- Operations research (18.05%)
What were the highlights of his more recent work (between 2015-2021)?
- Mathematical optimization (19.80%)
- Operations research (18.05%)
- Automotive engineering (3.51%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Mathematical optimization, Operations research, Automotive engineering, Disruption management and Transport engineering.
Hong Kam Lo is interested in Linear programming, which is a field of Mathematical optimization.
His Operations research research includes themes of Probability distribution, Reliability, Social network, Fleet management and Speed limit.
His Automotive engineering study combines topics from a wide range of disciplines, such as Cost curve and Normalization.
The Transport engineering study combines topics in areas such as Subdivision, Profitability index and Service.
His work in Traffic simulation covers topics such as Overtaking which are related to areas like Traffic flow.
Between 2015 and 2021, his most popular works were:
- Two-phase stochastic program for transit network design under demand uncertainty (44 citations)
- Day-to-day departure time modeling under social network influence (34 citations)
- Two-way-looking self-equalizing headway control for bus operations (26 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Mathematical optimization
- Information technology
Hong Kam Lo mostly deals with Operations research, Mathematical optimization, Bayesian network, Network planning and design and Stochastic programming.
His research integrates issues of Reliability, Pricing strategies, Travel behavior and Operations management in his study of Operations research.
His work on Linear programming as part of general Mathematical optimization research is often related to SIGNAL, thus linking different fields of science.
His studies in Bayesian network integrate themes in fields like Graphical model, Probabilistic logic and Sensitivity.
His Network planning and design study integrates concerns from other disciplines, such as Column generation, Public transport and Robustness.
His Stochastic programming research integrates issues from Base, Reliability, Adaptive control and Online algorithm.
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