Abstract: This talk presents 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.

Biography: ALI WAGDY MOHAMED received his B.Sc., M.Sc. and PhD. degrees from Cairo University, in 2000, 2004 and 2010, respectively. Ali Wagdy is an Associate Professor at Operations Research department, Faculty of Graduate Studies for Statistical Research), Cairo University, Egypt. Currently, He is an Associate Professor of Statistics at Wireless Intelligent Networks Center (WINC), Faculty of Engineering and Applied Sciences, Nile University. Recently, he has recognized among the top 2% scientists according to Stanford University report 2019. He serves as reviewer of more than 70 international accredited top-tier journals and has been awarded the Publons Peer Review Awards 2018, for placing in the top 1% of reviewers worldwide in assorted field. He is an associate editor with Swarm and Evolutionary Computation Journal, Elsevier. He is editor in more than 10 journals of information sciences, applied mathematics, Engineering, system science and Operations Research. He has presented and participated in more than 5 international conferences. He participated as a member of the reviewer committee for 35 different conferences sponsored by Springer and IEEE. He has obtained Rank 3 in CEC’17 competitions on single objective bound constrained real-parameter numerical optimization in Proc of IEEE Congress on Evolutionary Computation, IEEE-CEC 2017, San Sebastián, Spain. Besides, Obtained Rank 3 and Rank 2 in CEC’18 competitions on single objective bound constrained real-parameter numerical optimization and Competition on Large scale global optimization, in Proc of IEEE Congress on Evolutionary Computation, IEEE-CEC 2017, Sao Paolo, Brazil. He published more than 55 papers in reputed and high impact journals like Information Sciences, Swarm and Evolutionary Computation, Computers & Industrial Engineering, Intelligent Manufacturing, Soft Computing and International Journal of Machine Learning and Cybernetics. He is interested in mathematical and statistical modeling, stochastic and deterministic optimization, swarm intelligence and evolutionary computation. Additionally, he is also interested in real world problems such as industrial, transportation, manufacturing, education and capital investment problems. 2 PhD and 1 master have been completed under his supervision.