A Comparative Study of Sine Cosine Optimizer and Its Variants for Engineering Design Problems

Abstract

Sine Cosine Algorithm (SCA) is one of the simplest optimization algorithms and is used to solve a wide range of problems due to using two simple mathematical equations. However, it faces local optima stagnation because of the constraints in its exploration and exploitation mechanism. To solve this problem, many researchers proposed new versions of sine cosine algorithm (SCA). The main concept of developing SCA performance is to add some methods or layers to original SCA, edit the SCA parameters, or only hybridize it with other optimization algorithms to improve SCA’s exploration and exploitation. SCA and three new SCA variants were applied to solve three constrained engineering design problems in this study. The outcomes show that SCA was still able to report a good result more than some of its variants.