What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Management
- Algorithm
The scientist’s investigation covers issues in Mathematical optimization, Evolutionary algorithm, Differential evolution, Constrained optimization and Benchmark.
His Mathematical optimization study integrates concerns from other disciplines, such as Algorithm and Crossover.
His study in the field of Algorithm design also crosses realms of Code.
His Evolutionary algorithm research includes themes of Evolutionary computation and Multi-objective optimization.
His work carried out in the field of Differential evolution brings together such families of science as Optimization problem, Engineering optimization, CMA-ES and Metaheuristic.
His Constrained optimization study combines topics from a wide range of disciplines, such as Feasible region and Evolution strategy.
His most cited work include:
- Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters (890 citations)
- Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization (397 citations)
- A Multiobjective Optimization-Based Evolutionary Algorithm for Constrained Optimization (303 citations)
What are the main themes of his work throughout his whole career to date?
Yong Wang mainly investigates Mathematical optimization, Evolutionary algorithm, Differential evolution, Evolutionary computation and Multi-objective optimization.
His biological study spans a wide range of topics, including Algorithm and Benchmark.
His Evolutionary algorithm study combines topics in areas such as Feasible region, Genetic algorithm, Selection, Optimization problem and Crossover.
His research investigates the connection between Differential evolution and topics such as CMA-ES that intersect with issues in Covariance matrix.
Many of his research projects under Multi-objective optimization are closely connected to Decomposition and Electronic mail with Decomposition and Electronic mail, tying the diverse disciplines of science together.
His Constrained optimization study which covers Evolutionary programming that intersects with Imperialist competitive algorithm.
He most often published in these fields:
- Mathematical optimization (50.00%)
- Evolutionary algorithm (44.64%)
- Differential evolution (25.89%)
What were the highlights of his more recent work (between 2018-2021)?
- Mathematical optimization (50.00%)
- Evolutionary algorithm (44.64%)
- Differential evolution (25.89%)
In recent papers he was focusing on the following fields of study:
Yong Wang focuses on Mathematical optimization, Evolutionary algorithm, Differential evolution, Optimization problem and Linear programming.
His Mathematical optimization research focuses on subjects like Nonlinear system, which are linked to Mutation.
His research in Evolutionary algorithm intersects with topics in Evolutionary computation, Feasible region, Constrained optimization and Pattern recognition.
His Differential evolution research is within the category of Algorithm.
He interconnects Centralized computing and Resource allocation in the investigation of issues within Optimization problem.
His work investigates the relationship between Linear programming and topics such as Local optimum that intersect with problems in Dimensionality reduction, Feature selection, Search algorithm and Classifier.
Between 2018 and 2021, his most popular works were:
- Finding Multiple Roots of Nonlinear Equation Systems via a Repulsion-Based Adaptive Differential Evolution (40 citations)
- Global and Local Surrogate-Assisted Differential Evolution for Expensive Constrained Optimization Problems With Inequality Constraints (40 citations)
- Composite Differential Evolution for Constrained Evolutionary Optimization (38 citations)
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