World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
6051
World Ranking
10731
National Ranking
194

Overview

Peter A. N. Bosman is affiliated with the Centrum Wiskunde & Informatica in the Netherlands. Their research primarily focuses on the field of Computer Science, with 192 publications documented in this area.

Their work spans several subfields, notably:

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Pulmonary and Respiratory Medicine
  • Radiology, Nuclear Medicine and Imaging

The main topics of their research include:

  • Metaheuristic Optimization Algorithms Research
  • Advanced Multi-Objective Optimization Algorithms
  • Evolutionary Algorithms and Applications
  • Advanced Radiotherapy Techniques
  • Machine Learning and Data Classification
  • Prostate Cancer Diagnosis and Treatment
  • Advanced Neural Network Applications

Peter A. N. Bosman has published extensively in various venues, among which the most frequent are:

  • arXiv (Cornell University)
  • Radiotherapy and Oncology
  • Proceedings of the Genetic and Evolutionary Computation Conference
  • Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • Brachytherapy

Recent publications illustrate the range and depth of their contributions:

  • "Interactive Education on Sleep Hygiene with a Social Robot at a Pediatric Oncology Outpatient Clinic: Feasibility, Experiences, and Preliminary Effectiveness", 2022, published in Cancers
  • "Local Search is a Remarkably Strong Baseline for Neural Architecture Search", 2021, published in Lecture notes in computer science
  • "A Novel Approach to Designing Surrogate-assisted Genetic Algorithms by Combining Efficient Learning of Walsh Coefficients and Dependencies", 2021, published in ACM Transactions on Evolutionary Learning and Optimization
  • "Achieving Highly Scalable Evolutionary Real-Valued Optimization by Exploiting Partial Evaluations", 2020, published in Evolutionary Computation
  • "Machine learning for the prediction of pseudorealistic pediatric abdominal phantoms for radiation dose reconstruction", 2020, published in Journal of Medical Imaging

The scientist collaborates regularly with several co-authors, including:

  • Tanja Alderliesten
  • Arkadiy Dushatskiy
  • Marco Virgolin
  • Anton Bouter
  • Bradley R. Pieters

Best Publications

  • The balance between proximity and diversity in multiobjective evolutionary algorithms

    P.A.N. Bosman;D. Thierens

  • Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA

    Peter A. N. Bosman;Dirk Thierens

  • Improving Model-Based Genetic Programming for Symbolic Regression of Small Expressions.

    Marco Virgolin;Tanja Alderliesten;Cees Witteveen;Peter A. N. Bosman

  • Optimal mixing evolutionary algorithms

    Dirk Thierens;Peter A.N. Bosman

  • Continuous iterated density estimation evolutionary algorithms within the IDEA framework

    P.A.N. Bosman;D. Thierens

  • On Gradients and Hybrid Evolutionary Algorithms for Real-Valued Multiobjective Optimization

    P. A. N. Bosman

  • Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms

    Peter A.N. Bosman;Dirk Thierens

  • Linkage information processing in distribution estimation algorithms

    Peter A. N. Bosman;Dirk Thierens

  • Exploiting gradient information in numerical multi--objective evolutionary optimization

    Peter A. N. Bosman;Edwin D. de Jong

  • Learning, anticipation and time-deception in evolutionary online dynamic optimization

    Peter A. N. Bosman

  • Proceedings of the Genetic and Evolutionary Computation Conference - GECCO - 2006

    M. Keijzer;H. Lipson;P.A.N. Bosman;not Cwi

  • Multi-objective optimization of wind farm layouts – Complexity, constraint handling and scalability

    S.F. Rodrigues;Pavol Bauer;Peter Bosman

  • The correlation-triggered adaptive variance scaling IDEA

    Jörn Grahl;Peter A.N. Bosman;Franz Rothlauf

  • Design and Application of iterated Density-Estimation Evolutionary Algorithms

    P.A.N. Bosman

  • Enhancing the Performance of Maximum---Likelihood Gaussian EDAs Using Anticipated Mean Shift

    Peter A. Bosman;Jörn Grahl;Dirk Thierens

  • Hierarchical problem solving with the linkage tree genetic algorithm

    Dirk Thierens;Peter A.N. Bosman

  • The naive MIDEA: a baseline multi-objective EA

    Peter A. N. Bosman;Dirk Thierens

  • Multi-objective mixture-based iterated density estimation evolutionary algorithms

    Dirk Thierens;Peter A. N. Bosman

  • Agent-based patient admission scheduling in hospitals

    Anke K. Hutzschenreuter;Peter A. N. Bosman;Ilona Blonk-Altena;Jan van Aarle

  • An algorithmic framework for density estimation based evolutionary algorithms

    P.A.N. Bosman;D. Thierens

  • Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case

    Peter A. N. Bosman;Han La Poutré

Frequent Co-Authors

Dirk Thierens
Dirk Thierens Utrecht University
Pavol Bauer
Pavol Bauer Delft University of Technology
Ann Nowé
Ann Nowé Vrije Universiteit Brussel
Martine De Cock
Martine De Cock University of Washington
Stefan Minner
Stefan Minner Technical University of Munich
Pascal Bouvry
Pascal Bouvry University of Luxembourg
Samee U. Khan
Samee U. Khan Mississippi State University
Wiro J. Niessen
Wiro J. Niessen Erasmus University Rotterdam

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