Tent Map based Optimization Method

In the real life, some problems cannot be solved using mathematical methods. Meta-heuristic optimization methods are usually used to solve these problems. One of the solutions used to increase the performance of meta-heuristic optimization methods is the use of chaotic maps. Chaos is a phenomenon of nonlinear methods. In this article, a new chaotic optimization method is proposed by using a tent map which is one of the frequently used chaotic maps. The proposed method is a particle-based method, which consists of random particle creation, best-fit calculation, particle update, and best-value update. The tent map is used during the particle update phase. In order to test the performance of the proposed method, 12 numerical comparison functions, which are frequently used in the literature, were used and the results obtained were compared with previously proposed and widely used optimization methods in the literature. Experimental results and comparisons show that the proposed method is a successful optimization method