World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
10198
World Ranking
7112
National Ranking
428

Overview

Ender Özcan is affiliated with the University of Nottingham in the United Kingdom. Their research spans multiple fields primarily in Engineering and Computer Science, with significant focus on subfields such as Industrial and Manufacturing Engineering, Artificial Intelligence, and Computational Theory and Mathematics.

Their work includes contributions to Management Science and Operations Research as well as Mechanics of Materials. The research topics covered by Özcan consistently revolve around optimization and decision-making methods. Key areas of study include:

  • Metaheuristic Optimization Algorithms Research
  • Advanced Multi-Objective Optimization Algorithms
  • Vehicle Routing Optimization Methods
  • Evolutionary Algorithms and Applications
  • Topology Optimization in Engineering
  • Multi-Criteria Decision Making
  • Advanced Manufacturing and Logistics Optimization

Özcan has published frequently in a set of journals and venues that reflect their research domains. The venues with multiple publications include:

  • Applied Soft Computing
  • Expert Systems with Applications
  • Information Sciences
  • Swarm and Evolutionary Computation
  • Complex & Intelligent Systems

The collaboration network of Özcan includes several frequent co-authors, indicating sustained partnerships in their research projects. These co-authors include:

  • Simon Woodward
  • Muhammet Deveci
  • G. Ntourmas
  • Dimitrios Chronopoulos
  • Fernaß Daoud

Among their recent published works, notable papers include:

  • "Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS," 2021, Applied Soft Computing
  • "A study on offshore wind farm siting criteria using a novel interval-valued fuzzy-rough based Delphi method," 2020, Journal of Environmental Management
  • "A Decision Support System for Assessing and Prioritizing Sustainable Urban Transportation in Metaverse," 2022, IEEE Transactions on Fuzzy Systems
  • "A multimodal particle swarm optimization-based approach for image segmentation," 2020, Expert Systems with Applications
  • "Interval type-2 fuzzy sets improved by Simulated Annealing for locating the electric charging stations," 2020, Information Sciences

Özcan's contributions predominantly intersect the development of algorithmic and computational techniques for optimization problems, with applications in transportation, energy systems, image processing, and urban infrastructure planning.

Best Publications

  • Hyper-heuristics: a survey of the state of the art

    Edmund K. Burke;Michel Gendreau;Matthew R. Hyde;Graham Kendall

  • A Classification of Hyper-heuristic Approaches

    Edmund K. Burke;Matthew Hyde;Graham Kendall;Gabriela Ochoa

  • Particle swarm optimization: surfing the waves

    E. Ozcan;C.K. Mohan

  • A comprehensive analysis of hyper-heuristics

    Ender Özcan;Burak Bilgin;Emin Erkan Korkmaz

  • Exploring Hyper-heuristic Methodologies with Genetic Programming

    Edmund K. Burke;Mathew R. Hyde;Graham Kendall;Gabriela Ochoa

  • Analysis of a simple particle swarm optimization system

    Ender Ozcan;Chilukuri K. Mohan

  • Recent Advances in Selection Hyper-heuristics

    John H. Drake;Ahmed Kheiri;Ender Özcan;Edmund K. Burke

  • 2015 IEEE Symposium Series on Computational Intelligence

    Honorary Chairs;Jacek Zurada;Andries Engelbrecht;Mengjie Zhang

  • An experimental study on hyper-heuristics and exam timetabling

    Burak Bilgin;Ender Özcan;Emin Erkan Korkmaz

  • A Classification of Hyper-Heuristic Approaches: Revisited

    Edmund K. Burke;Matthew R. Hyde;Graham Kendall;Gabriela Ochoa

  • A Reinforcement Learning-Great-Deluge Hyper-Heuristic for Examination Timetabling

    Ender Özcan;Mustafa Misir;Gabriela Ochoa;Edmund K. Burke

  • A Decision Support System for Assessing and Prioritizing Sustainable Urban Transportation in Metaverse

    Unknown

  • Offshore wind farm site selection using interval rough numbers based Best-Worst Method and MARCOS

    Muhammet Deveci;Ender Özcan;Robert I. John;Dragan Pamucar

  • Combining Monte-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem

    Shahriar Asta;Daniel Karapetyan;Ahmed Kheiri;Ender Özcan

  • A study on offshore wind farm siting criteria using a novel interval-valued fuzzy-rough based Delphi method

    Muhammet Deveci;Muhammet Deveci;Ender Özcan;Robert John;Catalin-Felix Covrig

  • Memetic algorithms for timetabling

    A. Alkan;E. Ozcan

  • A multi-objective hyper-heuristic based on choice function

    Mashael Maashi;Ender Özcan;Graham Kendall;Graham Kendall

  • Multi-objective evolutionary algorithms and hyper-heuristics for wind farm layout optimisation

    Wenwen Li;Ender Özcan;Robert John

  • A multi-agent based cooperative approach to scheduling and routing

    Simon Martin;Djamila Ouelhadj;Patrick Beullens;Ender Ozcan

  • Monte Carlo hyper-heuristics for examination timetabling

    Edmund K. Burke;Graham Kendall;Mustafa Mısır;Ender Özcan

  • a r einforcement l earning: Great- deluge h yper- h euristic for examination t imetabling

    Ender Özcan;Edmund K. Burke

Frequent Co-Authors

Edmund K. Burke
Edmund K. Burke Bangor University
Robert John
Robert John University of Nottingham
Graham Kendall
Graham Kendall MILA University
Gabriela Ochoa
Gabriela Ochoa University of Stirling
Chilukuri K. Mohan
Chilukuri K. Mohan Syracuse University
Isaac Triguero
Isaac Triguero University of Nottingham
Dragan Pamučar
Dragan Pamučar University of Belgrade
Rong Qu
Rong Qu University of Nottingham
Frank Hutter
Frank Hutter University of Freiburg

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