Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization

Faculty Computer Science Year: 2015
Type of Publication: ZU Hosted Pages:
Authors:
Journal: Applied Soft Computing ELSEVEIR Volume:
Keywords : Training , Testing , Self-Adaptive Multi-Operator Evolutionary Algorithm    
Abstract:
Over the last two decades, many different evolutionary algorithms (EAs) have been introduced for solving constrained optimization problems (COPs). Due to the variability of the characteristics in different COPs, no single algorithm performs
   
     
 
       

Author Related Publications

  • Saber Mohamed, "An Improved Self-Adaptive Differential Evolution Algorithm for Optimization Problems", IEEE, 2013 More
  • Saber Mohamed, "Differential Evolution with Dynamic Parameters Selection for Optimization Problems", IEEE, 2014 More
  • Saber Mohamed, "A Self-Adaptive Combined Strategies Algorithm for Constrained Optimization using Differential Evolution", ELSEVIER, 2014 More
  • Saber Mohamed, "Self-adaptive Mix of Particle Swarm Methodologies for Constrained Optimization", ELSEVIER, 2014 More
  • Saber Mohamed, "Adaptive Configuration of Evolutionary Algorithms for Constrained Optimization", ELSEVIER, 2013 More

Department Related Publications

  • Noha Mohamed Ibrahiem Mohamed Hamza, "A constraint consensus memetic algorithm for solving constrained optimization problems", Taylor & Francis, 2014 More
  • Saber Mohamed, "A surrogate-assisted differential evolution algorithm with dynamic parameters selection for solving expensive optimization problems", IEEE, 2014 More
  • Saber Mohamed, "Differential Evolution Combined with Constraint Consensus for Constrained Optimization", IEEE, 2011 More
  • Mohammed Abdel Basset Metwally Attia, "An Interactive Multi-Criteria Decision-Making Approach for Autonomous Vehicles and Distributed Resources Based on Logistic Systems: Challenges for a Sustainable Future", MDPI, 2023 More
  • Mohammed Abdel Basset Metwally Attia, "Optimal selection of battery recycling plant location: strategies, challenges, perspectives, and sustainability", Springer Nature, 2023 More
Tweet