Using Hybrid Dependency Identification with a Memetic Algorithm for Large Scale Optimization Problems

Faculty Computer Science Year: 2012
Type of Publication: ZU Hosted Pages: 168-177
Authors:
Eman samir hasan sayed
Journal: Simulated Evolution and Learning Springer Berlin Heidelberg Volume: 0302-9743
Keywords : Using Hybrid Dependency Identification with , Memetic    
Abstract:
Decomposing a large scale problem into smaller subproblems is one of the approaches used to overcome the usual performance deterioration that occurs in EA because of the large dimensionality. To achieve a good performance with a decompositi
    
     
 
       

Author Related Publications

  • Eman samir hasan sayed, "Decision Making Assessment for Site Selection Using the AHP and TOPSIS Methods", Statistical studies institution, Cairo University, Egypt, 2007 More
  • Eman samir hasan sayed, "Dependency Identification technique for large scale optimization problems", IEEE, 2012 More
  • Eman samir hasan sayed, "A Decomposition-based Algorithm for Dynamic Economic Dispatch Problems", IEEE, 2014 More
  • Eman samir hasan sayed, "Decomposition-based evolutionary algorithm for large scale constrained problems", Elsevier Inc, 2014 More
  • Eman samir hasan sayed, "Large Scale Optimization based on self-directed Local Search", ASOR Bulletin, 2011 More

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  • Eman samir hasan sayed, "Decision Making Assessment for Site Selection Using the AHP and TOPSIS Methods", Statistical studies institution, Cairo University, Egypt, 2007 More
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