Seeker Evolutionary Algorithm (SEA): a Novel Algorithm for ContinuousOptimization

Nowadays, in majority of academic contexts, it has been tried to consider the highest possible level ofsimilarities to the real world. Hence, most of the problems have complicated structures. Traditionalmethods for solving almost all of the mathematical and optimization problems are inefficient. As aresult, meta-heuristic algorithms have been employed increasingly during recent years. In this study, anew algorithm, namely Seeker Evolutionary Algorithm (SEA), is introduced for solving continuousmathematical problems, which is based on a group seeking logic. In this logic, the seeking region andthe seekers located inside are divided into several sections and they seek in that special area. In order toassess the performance of this algorithm, from the available samples in papers, the most visitedalgorithms have been employed. The obtained results show the advantage of the proposed SEA incomparison to these algorithms. At the end, a mathematical problem is designed, which is unlike thestructure of meta-heuristic algorithms. All the prominent algorithms are applied to solve this problem,and none of them is able to solve.