What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Algorithm
- Genetic algorithm
His scientific interests lie mostly in Mathematical optimization, Optimization problem, Meta-optimization, Multi-swarm optimization and Derivative-free optimization.
His work on Metaheuristic and Genetic algorithm as part of general Mathematical optimization study is frequently linked to Boundary value problem, therefore connecting diverse disciplines of science.
His Genetic algorithm research is multidisciplinary, incorporating perspectives in Topology, Particle swarm optimization, Ant colony optimization algorithms and Differential evolution.
His research integrates issues of Disc brake and Selection in his study of Optimization problem.
Ali Rıza Yıldız interconnects Algorithm design and Probabilistic-based design optimization in the investigation of issues within Derivative-free optimization.
The various areas that he examines in his Probabilistic-based design optimization study include Continuous optimization and Engineering optimization.
His most cited work include:
- Cuckoo search algorithm for the selection of optimal machining parameters in milling operations (312 citations)
- Comparison of evolutionary-based optimization algorithms for structural design optimization (225 citations)
- A novel particle swarm optimization approach for product design and manufacturing. (192 citations)
What are the main themes of his work throughout his whole career to date?
Mathematical optimization, Metaheuristic, Optimization problem, Optimization algorithm and Multi-swarm optimization are his primary areas of study.
His studies in Meta-optimization, Genetic algorithm, Engineering optimization, Derivative-free optimization and Search algorithm are all subfields of Mathematical optimization research.
His Genetic algorithm research is multidisciplinary, incorporating elements of Sorting, Particle swarm optimization and Differential evolution.
His work carried out in the field of Optimization problem brings together such families of science as Cuckoo search, Artificial bee colony algorithm, Ant colony optimization algorithms and Reliability engineering.
Ali Rıza Yıldız works mostly in the field of Optimization algorithm, limiting it down to topics relating to Algorithm and, in certain cases, Benchmark, as a part of the same area of interest.
His study in Taguchi methods extends to Multi-swarm optimization with its themes.
He most often published in these fields:
- Mathematical optimization (55.56%)
- Metaheuristic (29.63%)
- Optimization problem (29.63%)
What were the highlights of his more recent work (between 2018-2021)?
- Mathematical optimization (55.56%)
- Optimization algorithm (20.99%)
- Metaheuristic (29.63%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Mathematical optimization, Optimization algorithm, Metaheuristic, Algorithm and Automotive engineering.
In general Mathematical optimization study, his work on Optimization problem and Swarm behaviour often relates to the realm of Constraint, thereby connecting several areas of interest.
His Optimization problem research is multidisciplinary, incorporating perspectives in Particle swarm optimization, Cuckoo search, Ant colony optimization algorithms, Artificial bee colony algorithm and Robustness.
His biological study spans a wide range of topics, including Nelder–Mead method, Shape optimization and Control theory.
His Metaheuristic research incorporates elements of Evolutionary algorithm, Differential evolution and Cam follower.
Ali Rıza Yıldız has researched Algorithm in several fields, including Dragonfly algorithm and Spur gear.
Between 2018 and 2021, his most popular works were:
- A Comparative Study of Recent Non-traditional Methods for Mechanical Design Optimization (59 citations)
- The Harris hawks optimization algorithm, salp swarm algorithm, grasshopper optimization algorithm and dragonfly algorithm for structural design optimization of vehicle components (55 citations)
- A new hybrid Harris hawks-Nelder-Mead optimization algorithm for solving design and manufacturing problems (50 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Algorithm
- Artificial intelligence
The scientist’s investigation covers issues in Optimization algorithm, Mathematical optimization, Algorithm, Automotive engineering and Salp swarm algorithm.
The concepts of his Optimization algorithm study are interwoven with issues in Nelder–Mead method, Manufacturing operations and Selection.
His Mathematical optimization study is mostly concerned with Optimization problem and Particle swarm optimization.
His studies in Optimization problem integrate themes in fields like Rate of convergence, Artificial bee colony algorithm, Genetic algorithm and Search algorithm.
His research in the fields of Brake overlaps with other disciplines such as Solubility, Connecting rod and Sensor system.
His research in Salp swarm algorithm intersects with topics in Convergence, Water cycle algorithm and Robustness.
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