What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Algorithm
- Statistics
His main research concerns Mathematical optimization, Constrained optimization, Nonlinear programming, Derivative-free optimization and Algorithm.
His Mathematical optimization research integrates issues from Iterated function and Limit point.
The various areas that he examines in his Iterated function study include Minification, Dense set, Finite set and Nonlinear system.
His work investigates the relationship between Constrained optimization and topics such as Class that intersect with problems in Smoothness, Relation and Regular polygon.
The Derivative-free optimization study combines topics in areas such as Vector optimization, Lagrangian relaxation, Surrogate model and Continuous optimization.
His Algorithm research incorporates elements of Quadratic equation, Quadratically constrained quadratic program and Linearization.
His most cited work include:
- Mesh Adaptive Direct Search Algorithms for Constrained Optimization (865 citations)
- Analysis of Generalized Pattern Searches (768 citations)
- A Pattern Search Filter Method for Nonlinear Programming without Derivatives (244 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Mathematical optimization, Algorithm, Optimization problem, Combinatorics and Direct search.
His study in Constrained optimization, Derivative-free optimization, Multi-objective optimization, Pattern search and Quadratic programming falls under the purview of Mathematical optimization.
His Constrained optimization research includes elements of Iterated function, Nonlinear programming, Class, Limit point and Search algorithm.
As part of his studies on Algorithm, he often connects relevant areas like Finite set.
His work carried out in the field of Combinatorics brings together such families of science as Discrete mathematics, Linear programming, Regular polygon and Polygon.
When carried out as part of a general Direct search research project, his work on Direct search algorithm is frequently linked to work in Class, therefore connecting diverse disciplines of study.
He most often published in these fields:
- Mathematical optimization (56.39%)
- Algorithm (18.94%)
- Optimization problem (18.06%)
What were the highlights of his more recent work (between 2018-2021)?
- Mathematical optimization (56.39%)
- Algorithm (18.94%)
- Context (4.85%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Mathematical optimization, Algorithm, Context, Standard deviation and Multisearch.
His Mathematical optimization research incorporates themes from Variable and Computational intelligence.
His studies in Algorithm integrate themes in fields like Multivariate normal distribution, Feasible region, Constrained optimization and Maxima and minima.
His studies deal with areas such as Computation and Reduction as well as Standard deviation.
His research investigates the connection with Work and areas like Computational budget which intersect with concerns in Quadratic equation.
His Optimization problem study combines topics in areas such as Value, Optimization algorithm, Calibration and Direct search algorithm.
Between 2018 and 2021, his most popular works were:
- Performance indicators in multiobjective optimization (21 citations)
- The Mesh Adaptive Direct Search Algorithm for Granular and Discrete Variables (19 citations)
- StoMADS: Stochastic blackbox optimization using probabilistic estimates (4 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Statistics
- Algorithm
Charles Audet spends much of his time researching Mathematical optimization, Optimization problem, Algorithm, Dense set and Distribution.
He studies Mathematical optimization, namely Multi-objective optimization.
His Optimization problem research includes themes of Calibration, Optimization algorithm, Value and Direct search algorithm.
His research brings together the fields of Direct search and Algorithm.
Charles Audet has included themes like Probabilistic logic, Applied mathematics and Stationary point in his Dense set study.
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