Abu Zitar, Raed

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Name
Abu Zitar, Raed
Main Affiliation
Email
raed.zitar@sorbonne.ae
ORCID
0000-0003-2693-2132
Scopus Author ID
8858522100
Status
Currently affiliated

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  • Publication
    Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review
    (2023)
    Chakraborty, Sanjoy
    ;
    Saha, Apu Kumar
    ;
    Ezugwu, Absalom E.
    ;
    Agushaka, Jeffrey O.
    ;
    Abu Zitar, Raed 
    ;
    Abualigah, Laith
    Differential evolution (DE) is one of the highly acknowledged population-based optimization algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems. DE has grown steadily since its beginnings due to its ability to solve various issues in academics and industry. Different mutation techniques and parameter choices influence DE's exploration and exploitation capabilities, motivating academics to continue working on DE. This survey aims to depict DE's recent developments concerning parameter adaptations, parameter settings and mutation strategies, hybridizations, and multiobjective variants in the last twelve years. It also summarizes the problems solved in image processing by DE and its variants.
      24  10Scopus© Citations 4
  • Publication
    Gradient-Based Optimizer (GBO): A Review, Theory, Variants, and Applications
    (2023)
    Daoud, Mohammad Sh.
    ;
    Shehab, Mohammad
    ;
    Al-Mimi, Hani M.
    ;
    Abualigah, Laith
    ;
    Zitar, Raed 
    ;
    Shambour, Mohd Khaled Yousef
    This paper introduces a comprehensive survey of a new population-based algorithm so-called gradient-based optimizer (GBO) and analyzes its major features. GBO considers as one of the most effective optimization algorithm where it was utilized in different problems and domains, successfully. This review introduces set of related works of GBO where distributed into; GBO variants, GBO applications, and evaluate the efficiency of GBO compared with other metaheuristic algorithms. Finally, the conclusions concentrate on the existing work on GBO, showing its disadvantages, and propose future works. The review paper will be helpful for the researchers and practitioners of GBO belonging to a wide range of audiences from the domains of optimization, engineering, medical, data mining and clustering. As well, it is wealthy in research on health, environment and public safety. Also, it will aid those who are interested by providing them with potential future research.
      20