Mohamed, A. W., A. A. Hadi, and A. K. Mohamed,
Gaining-sharing knowledge based algorithm for solving optimization problems: a novel nature-inspired algorithm,
, vol. 11, issue 7, pp. 1501 - 1529, 2020.
AbstractThis paper proposes a novel nature-inspired algorithm called Gaining Sharing Knowledge based Algorithm (GSK) for solving optimization problems over continuous space. The GSK algorithm mimics the process of gaining and sharing knowledge during the human life span. It is based on two vital stages, junior gaining and sharing phase and senior gaining and sharing phase. The present work mathematically models these two phases to achieve the process of optimization. In order to verify and analyze the performance of GSK, numerical experiments on a set of 30 test problems from the CEC2017 benchmark for 10, 30, 50 and 100 dimensions. Besides, the GSK algorithm has been applied to solve the set of real world optimization problems proposed for the IEEE-CEC2011 evolutionary algorithm competition. A comparison with 10 state-of-the-art and recent metaheuristic algorithms are executed. Experimental results indicate that in terms of robustness, convergence and quality of the solution obtained, GSK is significantly better than, or at least comparable to state-of-the-art approaches with outstanding performance in solving optimization problems especially with high dimensions.
Ganesh, N., S. Jayalakshmi, R. C. Narayanan, M. Mahdal, H. M. Zawbaa, and A. W. Mohamed,
"Gated deep reinforcement learning with red deer optimization for medical image classification",
IEEE Access, vol. 11: IEEE, pp. 58982-58993, 2023.
Abstractn/a
El-Qulity, S. A., and A. W. Mohamed,
"A Generalized National Planning Approach for Admission Capacity in Higher Education: A Nonlinear Integer Goal Programming Model with a Novel Differential Evolution Algorithm",
Computational Intelligence and Neuroscience, vol. 2016: Hindawi Publishing Corporation, pp. 5207362, 2016.
AbstractThis paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness.
Chandrika, N. G., K. Alnowibet, S. K. Kautish, S. E. Reddy, A. F. Alrasheedi, and A. W. Mohamed,
"Graph Transformer for Communities Detection in Social Networks.",
Computers, Materials & Continua, vol. 70, issue 3, 2022.
Abstractn/a
Alnowibet, K. A., S. Mahdi, M. El-Alem, M. Abdelawwad, and A. W. Mohamed,
"Guided hybrid modified simulated annealing algorithm for solving constrained global optimization problems",
Mathematics, vol. 10, issue 8: MDPI, pp. 1312, 2022.
Abstractn/a