What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mathematical optimization
- Algorithm
His primary areas of study are Mathematical optimization, Lagrangian relaxation, Job shop scheduling, Scheduling and Artificial neural network.
His Mathematical optimization research is mostly focused on the topic Dynamic programming.
Peter B. Luh combines subjects such as Schedule, Job shop, Scheduling, Subgradient method and Production control with his study of Lagrangian relaxation.
His work deals with themes such as Lagrange multiplier and Control theory, which intersect with Subgradient method.
His research integrates issues of Electric power industry, Computational complexity theory, Power system simulation, Reservation price and Theory of computation in his study of Job shop scheduling.
Peter B. Luh has researched Artificial neural network in several fields, including Economic forecasting, Extended Kalman filter and Market clearing.
His most cited work include:
- Short-Term Load Forecasting: Similar Day-Based Wavelet Neural Networks (292 citations)
- Scheduling of manufacturing systems using the Lagrangian relaxation technique (220 citations)
- A practical approach to job-shop scheduling problems (204 citations)
What are the main themes of his work throughout his whole career to date?
Mathematical optimization, Lagrangian relaxation, Job shop scheduling, Scheduling and Scheduling are his primary areas of study.
His is doing research in Dynamic programming, Subgradient method, Integer programming, Optimization problem and Lagrange multiplier, both of which are found in Mathematical optimization.
His Integer programming study which covers Linear programming that intersects with Power system simulation.
His Lagrangian relaxation study combines topics from a wide range of disciplines, such as Tardiness, Stochastic programming, Schedule, Convergence and Production control.
His study on Job shop scheduling is mostly dedicated to connecting different topics, such as Heuristics.
His Scheduling course of study focuses on Operations research and Emergency evacuation and Process.
He most often published in these fields:
- Mathematical optimization (55.80%)
- Lagrangian relaxation (33.57%)
- Job shop scheduling (16.18%)
What were the highlights of his more recent work (between 2012-2021)?
- Mathematical optimization (55.80%)
- Lagrangian relaxation (33.57%)
- Power system simulation (7.97%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Mathematical optimization, Lagrangian relaxation, Power system simulation, Simulation and Linear programming.
His biological study spans a wide range of topics, including Renewable energy and Economic dispatch.
Peter B. Luh has included themes like Convergence, Lagrange multiplier, Asynchronous communication and Reduction in his Lagrangian relaxation study.
Within one scientific family, Peter B. Luh focuses on topics pertaining to Transmission under Power system simulation, and may sometimes address concerns connected to Reliability.
His Simulation research includes themes of Social force model, Emergency evacuation and Energy accounting.
His Job shop scheduling research extends to the thematically linked field of Scheduling.
Between 2012 and 2021, his most popular works were:
- Building Energy Management: Integrated Control of Active and Passive Heating, Cooling, Lighting, Shading, and Ventilation Systems (167 citations)
- Very Short-Term Load Forecasting: Wavelet Neural Networks With Data Pre-Filtering (148 citations)
- Operation optimization of a distributed energy system considering energy costs and exergy efficiency (119 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mathematical optimization
- Algorithm
Peter B. Luh mainly focuses on Mathematical optimization, Simulation, Renewable energy, Lagrangian relaxation and Power system simulation.
The various areas that Peter B. Luh examines in his Mathematical optimization study include Economic dispatch and Energy accounting.
His Simulation study also includes fields such as
- Distributed computing most often made with reference to Distributed generation,
- Optimization problem which connect with Solid modeling.
His Renewable energy research incorporates themes from Dynamic programming, Cogeneration and Reliability.
His study in Lagrangian relaxation is interdisciplinary in nature, drawing from both State variable, Time horizon and Job shop scheduling.
His Power system simulation study integrates concerns from other disciplines, such as Power transmission, Wind power, Robustness and Heat pump.
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