MOEO-EED: A multi-objective equilibrium optimizer with exploration–exploitation​ dominance strategy

Faculty Computer Science Year: 2021
Type of Publication: ZU Hosted Pages:
Authors:
Mohammed Abdel Basset Metwally Attia
Journal: Knowledge-Based Systems Elsevier Volume: 214
Keywords : MOEO-EED: , multi-objective equilibrium optimizer with exploration–exploitation​    
Abstract:
The work proposes multi-objective variants of the recently-proposed equilibrium optimizer (EO) using an archive to obtain Pareto optimal solutions and a crowding distance approach to preserve the diversity among the non-dominated solutions.
    
     
 
       

Author Related Publications

  • Mohammed Abdel Basset Metwally Attia, "Discrete greedy flower pollination algorithm for spherical traveling salesman problem", Springer, 2019 More
  • Mohammed Abdel Basset Metwally Attia, "A New Hybrid Flower Pollination Algorithm for Solving Constrained Global Optimization Problems", Natural Sciences Publishing Cor., 2014 More
  • Mohammed Abdel Basset Metwally Attia, "A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems", Springer London, 2021 More
  • Mohammed Abdel Basset Metwally Attia, "An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection", Pergamon, 2021 More
  • Mohammed Abdel Basset Metwally Attia, "An efficient teaching-learning-based optimization algorithm for parameters identification of photovoltaic models: Analysis and validations", Pergamon, 2021 More

Department Related Publications

  • Ibrahiem Mahmoud Mohamed Elhenawy, "BERT-CNN: A Deep Learning Model for Detecting Emotions from Text", Tech Science Press, 2021 More
  • Ahmed Raafat Abass Mohamed Saliem, "BERT-CNN: A Deep Learning Model for Detecting Emotions from Text", Tech Science Press, 2021 More
  • Ahmed Raafat Abass Mohamed Saliem, "Using General Regression with Local Tuning for Learning Mixture Models from Incomplete Data Sets", ScienceDirect, 2010 More
  • Ahmed Raafat Abass Mohamed Saliem, "On determining efficient finite mixture models with compact and essential components for clustering data", ScienceDirect, 2013 More
  • Ahmed Raafat Abass Mohamed Saliem, "Unsupervised learning of mixture models based on swarm intelligence and neural networks with optimal completion using incomplete data", ScienceDirect, 2012 More
Tweet