A comparative study of cuckoo search and flower pollination algorithm on solving global optimization problems

Faculty Computer Science Year: 2017
Type of Publication: ZU Hosted Pages:
Authors:
Laila Abdel Fattah Shawqi Ibrahim
Journal: Library Hi Tech emerald insight Volume:
Keywords : , comparative study , cuckoo search , , flower pollination    
Abstract:
Purpose The purpose of this paper is to present a comparison between two well-known Lévy-based meta-heuristics called cuckoo search (CS) and flower pollination algorithm (FPA). Design/methodology/approach Both the algorithms (Lévy-base
    
     
 
       

Author Related Publications

  • Laila Abdel Fattah Shawqi Ibrahim, "Elite opposition-flower pollination algorithm for quadratic assignment problem", IOS press, 2017 More
  • Laila Abdel Fattah Shawqi Ibrahim, "Metaheuristic Algorithms: A Comprehensive Review", Elsevier‏, 2018 More
  • Laila Abdel Fattah Shawqi Ibrahim, "A comprehensive study of cuckoo-inspired algorithms", Springer‏, 2018 More
  • Laila Abdel Fattah Shawqi Ibrahim, "An improved nature inspired meta-heuristic algorithm for 1-D bin packing problems", Springer‏, 2018 More
  • Laila Abdel Fattah Shawqi Ibrahim, "Grid quorum‐based spatial coverage in mobile wireless sensor networks using nature‐inspired firefly algorithm", John Wiley & Sons, 2019 More

Department 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
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  • Ahmed Raafat Abass Mohamed Saliem, "Using General Regression with Local Tuning for Learning Mixture Models from Incomplete Data Sets", ScienceDirect, 2010 More
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