What is he best known for?
The fields of study he is best known for:
- Statistics
- Mathematical optimization
- Control theory
His primary scientific interests are in Multi-objective optimization, Genetic algorithm, Mathematical optimization, Process engineering and Global optimization.
The Multi-objective optimization study combines topics in areas such as Engineering drawing, Volumetric flow rate, Sorting, Optimization problem and Chemical engineering.
Gade Pandu Rangaiah has included themes like Simulated annealing, Low-density polyethylene, Biological system, Jumping and Steam reforming in his Genetic algorithm study.
His studies link Benchmark with Mathematical optimization.
His Process engineering research is multidisciplinary, incorporating elements of Waste management, Heat exchanger, Range, Heat transfer and Retrofitting.
His research in Global optimization intersects with topics in Gibbs free energy minimization, Phase equilibrium and Estimation theory.
His most cited work include:
- Multi-objective optimization : techniques and applications in chemical engineering (131 citations)
- Retrofitting conventional column systems to dividing-Wall Columns (112 citations)
- Multiobjective optimization of steam reformer performance using genetic algorithm (101 citations)
What are the main themes of his work throughout his whole career to date?
Gade Pandu Rangaiah mostly deals with Process engineering, Multi-objective optimization, Mathematical optimization, Control theory and Genetic algorithm.
His Process engineering study incorporates themes from Scientific method, Distillation, Heat exchanger, Retrofitting and Process.
His Multi-objective optimization research incorporates elements of Evolutionary algorithm, Chemical engineering and Optimal design.
His Mathematical optimization study frequently links to adjacent areas such as Benchmark.
His work in the fields of Control theory, such as Control theory, Internal model and Nonlinear control, overlaps with other areas such as Process control.
His biological study spans a wide range of topics, including Sorting and Simulated annealing.
He most often published in these fields:
- Process engineering (32.33%)
- Multi-objective optimization (23.00%)
- Mathematical optimization (20.67%)
What were the highlights of his more recent work (between 2015-2021)?
- Process engineering (32.33%)
- Multi-objective optimization (23.00%)
- Scientific method (9.33%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Process engineering, Multi-objective optimization, Scientific method, Retrofitting and Mathematical optimization.
His Process engineering study combines topics from a wide range of disciplines, such as Ideal solution, Distillation, Extractive distillation, Process design and Heuristics.
His Multi-objective optimization research incorporates themes from Chemical engineering, Process, Process optimization, Evolutionary algorithm and Perspective.
His studies deal with areas such as Energy, Enhanced oil recovery and Chromatography as well as Scientific method.
Gade Pandu Rangaiah studied Retrofitting and Heat exchanger that intersect with Penalty method and Structural engineering.
His research on Mathematical optimization often connects related areas such as Benchmark.
Between 2015 and 2021, his most popular works were:
- Multi-objective optimization : techniques and applications in chemical engineering (131 citations)
- Application and Analysis of Methods for Selecting an Optimal Solution from the Pareto-Optimal Front obtained by Multiobjective Optimization (67 citations)
- Design of shell-and-tube heat exchangers for multiple objectives using elitist non-dominated sorting genetic algorithm with termination criteria (48 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Mathematical optimization
- Artificial intelligence
Gade Pandu Rangaiah mainly focuses on Multi-objective optimization, Process engineering, Mathematical optimization, Distillation and Scientific method.
His Multi-objective optimization research is multidisciplinary, relying on both Waste management, Petroleum and Chemical industry.
His Process engineering study frequently draws connections to adjacent fields such as Column.
His Mathematical optimization research includes themes of Design of experiments, Chemical process and Benchmark.
His Evolutionary algorithm research focuses on subjects like Global optimization, which are linked to Process.
He has included themes like Sorting, Chemical engineering, Process design and Optimal design in his Genetic algorithm study.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
