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  1. Mission of the Chapter

The chapter aims to promotes Operations Research in Egypt. It focuses on Virtually, Nature-Inspired Optimization Algorithms (NIOAs) that have been originally developed to overcome the challenges of global optimization problems such as nonlinearity, non-convexity, non-continuity, non-differentiability, and/or multimodality which traditional numerical optimization techniques had difficulties solving. Furthermore, through considerable developed algorithms and strategies, NIOAs have been experimentally proven as efficient, effective and robust with high quality solutions at a low computational cost. The past and on-going research in this field covers a wide range of topics from basic research to a huge number of real-world applications in science, engineering, industry, business, economics. However, the main common deficiency of NIOAs is their parameter tunings. Moreover, NIOAs have a good global exploration ability that can reach the region of global optimum, but it is slow at exploitation of the solution. Moreover, NIOAs performance decreases as search space dimensionality increases. Finally, the performance of NIOAs deteriorates significantly when the problems of premature convergence and/or stagnation occur.

To improve the global performance of NIOAs, a considerable number of research studies have been conducted. Consequently, the main objectives and potential outputs of this chapter are to present recent contributions and significant development, advanced issues, and challenges in the field of nature inspired optimization algorithms through organizing conferences and workshops in national and international levels to enhance and promote the exchange of knowledge, the collaborations and the interactions between researchers and industrials.

Proposed submissions should be original, unpublished, and should present novel in-depth fundamental research contributions either from a methodological perspective or from an application point of view. Topics of interest include, but are not only limited to:

  • Adaptive and self-adaptive variants of Nature-Inspired Optimization Algorithms, such as:
    • Gaining-Sharing Knowledge based algorithm
    • Particle swarm optimization
    • Differential evolution
    • Genetic algorithms
    • Ant colony optimization
  • Empirical analysis of Adaptive and self-adaptive variants using the up-to-date benchmarks.
  • Novel parameter control mechanisms.
  • Constrained single- multi- and many-objective optimization.
  • Theoretical analysis and complexity of unconstrained and single- multi- and many-objective optimization.
  • Memetic algorithms in unconstrained and constrained single- multi- and many-objective optimization.
  • Solving real-world engineering application, such as:
  • Electrical and power systems,
  • machine learning, Robotics and Expert Systems
  • Pattern recognition and Image processing,
  • Bioinformatics and bio-medical engineering,
  • Electronics and communication engineering,
  • Manufacturing Science and Operation Research
  1. Rationale

Our work and research have been used to tackle many real-world optimization problems in several sectors, including, Energy, Industry, Transportation, Communications, and the health sector. Some of these problems are listed below:

  • Determine the best parameters values for solar systems.
  • Design of novel frameworks/algorithms to find the best location(s) for building new factories and companies.
  • Design new frameworks/algorithms to solve the optimal power flow problem.

Also, we participated in many international conferences in operations research and optimization.  Indeed, we organized special session in highly ranked journals and conferences in the area of operations research, optimization, and evolutionary computation.

  1. Organization, Officers, and Members
Name Affiliation Country Email
Prof. Ali Wagdy Mohamed Operations Research Department, Faculty of Graduate Studies for Statistical Research, Cairo University Egypt
Prof. Said Ali Hassan


Department of Decision Support and Operations Research, Faculty of Computers and Artificial Intelligence, Cairo University Egypt
Prof. Motaz Khorshid


Department of Decision Support and Operations Research, Faculty of Computers and Artificial Intelligence, Cairo University Egypt
Dr. Ali Khater Mohamed Faculty of Computer Science, October University for Modern Sciences and Arts Egypt
Assistant prof. Awad Khireldin Air Transport management program, Singapore Institute of Technology (SIT), Singapore Egypt
Dr. Karam Mohamed Goda Sallam Operations Research and Decision Support Dept. Faculty of Computers and Informatics, Zagazig University Egypt

To join this Chapter, please email to Prof. Ali Wagdy Mohamed at