Mahrokh Javadi

M.Sc. Mahrokh Javadi

Faculty of Computer Science
Chair of Computational Intelligence
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.

 

Journal Papers

  • Mahrokh Javadi and Sanaz Mostaghim 
  •  Analysis of inter and intra-front operations multimodal multi-objective optimization problems
  • Accepted for publication In special issue of Natural Computing journal on Deterministic and Stochastic Methods for Multi-objective Optimization. To be published in 2022

 

Reviewed Conference Papers (peer-reviewed)

 

  • Mahrokh Javadi and Sanaz Mostaghim 
  • A Multi-objective Multimodal Evolutionary Algorithm Using a Novel Tournament and Environmental Selections
  • Accepted at the 2021 IEEE Symposium Series on Computational Intelligence (SSCI), IEEE Symposium on Multi-criteria Decision-Making, Orlando, USA, 2021 --> Link to video presentation 

 

  • Mahrokh Javadi and Sanaz Mostaghim
  • A Neighborhood-based Density Measure for Multimodal Multi-Objective Optimization
  • In: Ishibuchi H. et al. (eds) Evolutionary Multi-Criterion Optimization. EMO 2021. Pages 335-345. Lecture Notes in Computer Science, vol 12654. Springer, Cham. --> Link ,  Link to video presentation  (Source Code)

 

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

  

  • Mahrokh Javadi, Cristian Ramirez-Atencia and Sanaz Mostaghim
  • Combining Manhattan and Crowding distances in Decision Space for Multimodal and Multi-objective Optimization Problems
  •  In: Gaspar-Cunha A., Periaux J., Giannakoglou K.C., Gauger N.R., Quagliarella D., Greiner D. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 55. Springer, Cham., pp. 131-145, 2021  --> Link

 

  • Mahrokh Javadi, Heiner Zille and Sanaz Mostaghim
  • The effects of Crowding Distance and Mutation in Multimodal and Multi-objective Optimization Problems
  • In: Gaspar-Cunha A., Periaux J., Giannakoglou K.C., Gauger N.R., Quagliarella D., Greiner D. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 55. Springer, Cham., pp. 115-130, 2021  --> Link  (Source Code)

 

  • 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
  • In: 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
  • In: ACM Genetic and Evolutionary Computation Conference (GECCO) Companion, Pages 205-206, ACM, Prague, Czech Republic, July 2019 --> Link

 

 

Last Modification: 10.06.2022 - Contact Person:

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