Mahrokh Javadi

Mahrokh Javadi

Faculty of Computer Science
Gebäude 29, Universitätsplatz 2, 39106, Magdeburg, G29-016
Vita

Mahrokh Javadi is currently a Ph.D. student at the Computational Intelligence laboratory of the Otto-von-Guericke University in Magdeburg-Germany. She obtained her master's degree in Industrial Engineering ( Socio-economic Systems Engineering) from Sharif University of Technology (SUT), Tehran, Iran in 2015. Her research at Otto-von-Guericke University focuses on multimodal multi-objective optimization.

 

Reviewed Conference Papers (peer-reviewed)

  • Mahrokh Javadi, Cristian Ramirez-Atencia and Sanaz Mostaghim
  • A Novel Grid-based Crowding Distance for Multimodal Multi-objective Optimization
  • To appear in the Proceedings of IEEE Congress on Evolutionary Computation (CEC), World Congress on Computational Intelligence, Glasgow, UK, 2020 

 

  • Mahrokh Javadi, Cristian Ramirez-Atencia and Sanaz Mostaghim
  • Combining Manhattan and Crowding distances in Decision Space for Multimodal and Multi-objective Optimization Problems
  • In Springer ECCOMAS book series on Computational Methods in Applied Sciences, to appear in 2020

 

  • Mahrokh Javadi, Heiner Zille and Sanaz Mostaghim
  • The effects of Crowding Distance and Mutation in Multimodal and Multi-objective Optimization Problems
  • In Springer ECCOMAS book series on Computational Methods in Applied Sciences, to appear in 2020

 

  • Mahrokh Javadi, Cristian Ramirez-Atencia and Sanaz Mostaghim
  • Combining Manhattan and Crowding distances in Decision Space for Multimodal and Multi-objective Optimization Problems
  • accepted for publication in EUROGEN conference, September 2019 --> download

 

  • Mahrokh Javadi, Heiner Zille and Sanaz Mostaghim
  • The effects of Crowding Distance and Mutation in Multimodal and Multi-objective Optimization Problems
  • accepted for publication in EUROGEN conference, September 2019 --> download

 

  • Mahrokh Javadi, Heiner Zille and Sanaz Mostaghim
  • Modified Crowding Distance and Mutation for Multimodal Multi-Objective Optimization
  • ACM Genetic and Evolutionary Computation Conference (GECCO) Companion, Pages 211-212, ACM, Prague, Czech Republic, July 2019 --> Link

 

  • Marde Helbig, Heiner Zille, Mahrokh Javadi and Sanaz Mostaghim
  • Performance of Dynamic Algorithms on the Dynamic Distance Minimization Problem
  • ACM Genetic and Evolutionary Computation Conference (GECCO) Companion, Pages 205-206, ACM, Prague, Czech Republic, July 2019 --> Link

 

 

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