What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Mathematical optimization
Metaheuristic, Mathematical optimization, Firefly algorithm, Algorithm and Artificial intelligence are his primary areas of study.
Xin-She Yang has researched Metaheuristic in several fields, including Cuckoo search, Optimization problem, Multi-swarm optimization and Particle swarm optimization.
His Mathematical optimization study combines topics from a wide range of disciplines, such as Chaotic and Benchmark.
His Firefly algorithm research includes elements of Nonlinear programming, Nonlinear system, Algorithm design, Nature inspired algorithm and Continuous optimization.
His Algorithm research incorporates elements of Genetic algorithm and Heuristic.
His Artificial intelligence research incorporates themes from Swarm intelligence, Machine learning and Bat algorithm.
His most cited work include:
- Cuckoo Search via Lévy flights (3339 citations)
- Nature-Inspired Metaheuristic Algorithms (2590 citations)
- A New Metaheuristic Bat-Inspired Algorithm (2392 citations)
What are the main themes of his work throughout his whole career to date?
Xin-She Yang focuses on Mathematical optimization, Metaheuristic, Artificial intelligence, Algorithm and Firefly algorithm.
His research integrates issues of Nonlinear system and Benchmark in his study of Mathematical optimization.
His Metaheuristic research is multidisciplinary, incorporating elements of Particle swarm optimization, Cuckoo search and Bat algorithm.
His Artificial intelligence research is multidisciplinary, relying on both Swarm intelligence and Machine learning.
With his scientific publications, his incorporates both Algorithm and Pollination.
By researching both Firefly algorithm and Firefly protocol, Xin-She Yang produces research that crosses academic boundaries.
He most often published in these fields:
- Mathematical optimization (34.75%)
- Metaheuristic (33.57%)
- Artificial intelligence (24.59%)
What were the highlights of his more recent work (between 2016-2020)?
- Optimization problem (15.84%)
- Swarm intelligence (15.84%)
- Mathematical optimization (34.75%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Optimization problem, Swarm intelligence, Mathematical optimization, Metaheuristic and Algorithm.
His biological study spans a wide range of topics, including Harmony search, Stability, Metaheuristic optimization, Robot and Nonlinear system.
The Swarm intelligence study combines topics in areas such as Swarm robotics, Computational intelligence and Premature convergence.
His work in the fields of Bat algorithm, Firefly algorithm and Combinatorial optimization overlaps with other areas such as Key.
His Metaheuristic research is within the category of Artificial intelligence.
His work on Cuckoo search and Local search as part of his general Algorithm study is frequently connected to Pollination, thereby bridging the divide between different branches of science.
Between 2016 and 2020, his most popular works were:
- Bio-inspired computation: Where we stand and what's next (172 citations)
- New directional bat algorithm for continuous optimization problems (133 citations)
- A discrete firefly algorithm to solve a rich vehicle routing problem modelling a newspaper distribution system with recycling policy (80 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Machine learning
His primary scientific interests are in Optimization problem, Swarm intelligence, Mathematical optimization, Metaheuristic and Algorithm.
His work deals with themes such as Stability and Behavioral pattern, which intersect with Optimization problem.
His Swarm intelligence research integrates issues from Swarm robotics, Robot, Swarm behaviour and Computational intelligence.
His Metaheuristic study introduces a deeper knowledge of Artificial intelligence.
When carried out as part of a general Algorithm research project, his work on Continuous optimization is frequently linked to work in Pollination, therefore connecting diverse disciplines of study.
His studies in Firefly algorithm integrate themes in fields like Point, Analysis of algorithms and Benchmark.
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