Multi-Operator based Evolutionary Algorithms for Solving Constrained Optimization Problems.

Faculty Computer Science Year: 2011
Type of Publication: ZU Hosted Pages: 1877–1896
Authors:
Saber Mohamed
Journal: Computers and Operations Research ELSEVIER Volume:
Keywords : Multi-Operator based Evolutionary Algorithms , Solving Constrained    
Abstract:
Over the last two decades, many sophisticated evolutionary algorithms have been introduced for solving constrained optimization problems. Due to the variability of characteristics in different COPs, no single algorithm performs consistently
    
     
 
       

Author Related Publications

  • Saber Mohamed, "Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization", ELSEVEIR, 2015 More
  • 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

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 approach of TOPSIS technique for developing supplier selection with group decision making under type-2 neutrosophic number", Elsevier B.V., 2019 More
  • Mohammed Abdel Basset Metwally Attia, "Krill herd ‎algorithm based ‎on cuckoo ‎search for ‎solving ‎engineering ‎optimization ‎problems", Springer, 2019 More
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