Comparison of the 10, 30, 50 and 100 dimensional results of the Developed Tree Seed Algorithm

EasyChair Preprint no. 6015

Abstract

Tree Seed Algorithm (TSA) is a meta-heuristic continuous optimization algorithm inspired by nature. This algorithm was developed and 5 different equations of difference were added to the algorithm as a seed generation strategy in 2019. Because the basic state of TSA provides effective solutions for low-dimensional problems, it has been observed that there are some performance losses with the increase in the size of the problem. In this study, the seed production strategies were updated and the TSA algorithm was used to solve numerical functions of different sizes such as 10, 30, 50 and 100. The test results of the Tree Seed Algorithm were obtained and compared with some well-known optimization methods. In the experiments, CEC2015 comparison functions were used and the developed TSA was compared with some variants of TSA, artificial bee colony, particle swarm optimization and differential evolution algorithm, and experimental results were reported as mean, maximum, minimum solutions and standard deviation.

Keyphrases: comparison, dimensionality, experimental results, Tree-Seed Algorithm

@Booklet{EasyChair:6015,
  author = {İmral Güngör and Bülent Gürsel Emiroğlu},
  title = {Comparison of the 10, 30, 50 and 100 dimensional results of the Developed Tree Seed Algorithm},
  howpublished = {EasyChair Preprint no. 6015},

  year = {EasyChair, 2021}}