Logistics-Singer Map-Based A New Chaotic Sara Optimization Method

Abstract

Many problems in daily life cannot be solved by using classical mathematical methods for having an infinite solution space. Therefore, it is recommended to use meta heuristic optimization methods that reduce the infinite solution space and based on the mathematical prediction principle in solving similar problems. In order to increase the performance of meta-heuristic optimization methods, number generator and chaotic maps are used. In this article, a new method of chaotic optimization has been developed and logistic and singer maps are used in the proposed optimization method. In order to test the performance of the proposed method, 6 different benchmarking functions and 3 different swarm-based optimization methods were used. The proposed method has produced more optimum results for all functions. In this way, it has been tried to prevent the integration of swarm optimization methods into local solutions.