Abstract
Metaheuristic algorithms are nature-inspired, have been a high level of search techniques, designed for global search to efficiently large solution spaces to find optimal or near-optimal solutions unlike traditional algorithms. These algorithms strike a balance between a suitable solution and its search time. The appropriate solution is selected from a group of solutions during several cycles by applying certain rules or criteria. Exploration and Exploitation are the two common features used to solve the problem in any optimization method. Exploration is the stage of searching for solutions within the search space by expanding this field to unexplored areas, and exploitation focuses on search areas that may contain solutions close to optimal solutions. Metaheuristic algorithms have been recently spread to solve many complex problems in different fields due to their flexibility and simplicity. In this paper, the metaheuristic algorithms that have been designed during the last ten years are presented and classified according to their characteristics and fields of use.
Keyword: Metaheuristic Algorithms, Optimization Problems
