Research Area: Metaheuristic Computing
Optimization problems occur in the real-world industry, science, engineering, economics, and other real-life activities. These problems are usually complex and difficult to solve by ex-act search methods. The deep need for solving these problems has activated the emergence of a new class of algorithms called Metaheuristics. Metaheuristics proved to solve large problems faster in a reasonable time-bound. The past five decades have witnessed the emergence of many metaheuristics algorithms, many of these algorithms imitate a phenomenon in nature orindustry, e.g., genetic evolution in nature and annealing process in metallurgy. Metaheuristics algorithms vary in their design and search behavior, thus, showing different performance in solving problems in different research fields. Metaheuristics are mainly composed of two main categories of algorithms,Trajectory, and Population-based algorithms.
Name of the Researcher: Amr Abdelhafez
Name of the Supervisor(s): Enrique Alba
Year of Completion: 2020
University: University Of Malaga
Thesis Link: Home Page Url
