Using the Developed Conjugate Gradient Algorithm and the Sand Cat Swarm Optimization (SCSO) Algorithm to Improve the Performance of the Whale Optimization Algorithm (WOA)

In this paper, two distinct strategies were used to enhance problem-solving abilities. The first strategy involved developing a conjugate gradient algorithm such that a new parameter was extracted and proposed. The second strategy included Improving the Whale Algorithm (WOA) in two ways, the first using the community by taking advantage of the developed conjugate gradient algorithm that was extracted from the first strategy and obtaining the proposed algorithm (CG-WOA) that gives better results than the results from the original algorithm. The second method is to combine the sand cat swarm optimization algorithm (SCSO) with the whale optimization algorithm (WOA), and the proposed algorithm (SCSO-WOA) is obtained. The proposed algorithms (CG-WOA) and (SCSO-WOA) have many characteristics, including their ability to deal with complex optimization problems and their speed efficiency compared to the original algorithm. The diversity of exploration and exploitation operations in the proposed algorithm (SCSO-WOA) gives it the advantage of fast convergence, obtaining the global optimal solution, and avoiding falling into local solutions. The efficiency of the two algorithms (CG-WOA) and (SCSO-WOA) was tested on five standard test functions, so that better numerical results were obtained than the results of the original