What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Machine learning
His primary areas of investigation include Evolutionary computation, Evolutionary algorithm, Mathematical optimization, Artificial intelligence and Evolutionary programming.
His Evolutionary computation study integrates concerns from other disciplines, such as Optimization problem, Theoretical computer science, Nonlinear programming and Motion planning.
His biological study deals with issues like Algorithm, which deal with fields such as Arithmetic and Binary number.
His work on Genetic algorithm, Metaheuristic and Travelling salesman problem as part of general Mathematical optimization research is often related to Variable, thus linking different fields of science.
His study looks at the relationship between Artificial intelligence and topics such as Machine learning, which overlap with Adaptation.
His study in Human-based evolutionary computation, Interactive evolutionary computation and Java Evolutionary Computation Toolkit falls under the purview of Evolutionary programming.
His most cited work include:
- Genetic Algorithms + Data Structures = Evolution Programs (10910 citations)
- Handbook of Evolutionary Computation (2148 citations)
- How to Solve It: Modern Heuristics (1651 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Evolutionary algorithm, Evolutionary computation, Mathematical optimization, Artificial intelligence and Evolutionary programming.
His Evolutionary algorithm research focuses on subjects like Operations research, which are linked to Computational intelligence.
His studies deal with areas such as Memetic algorithm, Theoretical computer science, Nonlinear programming and Heuristics as well as Evolutionary computation.
Within one scientific family, Zbigniew Michalewicz focuses on topics pertaining to Algorithm under Mathematical optimization, and may sometimes address concerns connected to Function.
His studies examine the connections between Evolutionary programming and genetics, as well as such issues in Genetic representation, with regards to Cultural algorithm.
His study ties his expertise on Learnable Evolution Model together with the subject of Java Evolutionary Computation Toolkit.
He most often published in these fields:
- Evolutionary algorithm (43.89%)
- Evolutionary computation (37.93%)
- Mathematical optimization (30.72%)
What were the highlights of his more recent work (between 2013-2021)?
- Mathematical optimization (30.72%)
- Evolutionary algorithm (43.89%)
- Algorithm (15.36%)
In recent papers he was focusing on the following fields of study:
Zbigniew Michalewicz mostly deals with Mathematical optimization, Evolutionary algorithm, Algorithm, Metaheuristic and Particle swarm optimization.
His work carried out in the field of Evolutionary algorithm brings together such families of science as Evolutionary computation and Decision-making.
His primary area of study in Evolutionary computation is in the field of Evolutionary programming.
His work on Algorithm design is typically connected to Zoom as part of general Algorithm study, connecting several disciplines of science.
His Metaheuristic research focuses on Scheduling and how it connects with Operations research.
His studies in Particle swarm optimization integrate themes in fields like Local optimum, Swarm behaviour, Function and Local convergence.
Between 2013 and 2021, his most popular works were:
- Book review: particle swarm optimization for single objective continuous space problems: A review (253 citations)
- A comprehensive benchmark set and heuristics for the traveling thief problem (85 citations)
- Analysis of Stability, Local Convergence, and Transformation Sensitivity of a Variant of the Particle Swarm Optimization Algorithm (65 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Machine learning
His primary scientific interests are in Particle swarm optimization, Algorithm, Multi-swarm optimization, Local convergence and Metaheuristic.
His Algorithm research incorporates themes from Function and Swarm behaviour.
His Multi-swarm optimization research is multidisciplinary, incorporating perspectives in Stochastic process, Stochastic optimization, Random variable and Stability.
Zbigniew Michalewicz interconnects Local optimum, Stability and Sensitivity in the investigation of issues within Local convergence.
He has researched Metaheuristic in several fields, including Travelling salesman problem and Theoretical computer science.
His Travelling salesman problem research includes elements of Evolutionary computation, Global optimization, Local search, Performance metric and Ranking.
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