Optimization Search Using Hypercubes

Abiyev R. H., Tunay M.

4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020, İstanbul, Turkey, 22 - 24 October 2020 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/ismsit50672.2020.9255257
  • City: İstanbul
  • Country: Turkey
  • Keywords: evolutionary computing, hypercube optimization search, Search algorithms
  • Istanbul Gelisim University Affiliated: Yes


© 2020 IEEE.An optimization search algorithm for multivariate systems is proposed. The proposed optimization search algorithm includes initialization-, displacement-shrink- and searching areas stages. The initialization stage generates initial solutions in the search area that represented by hypercube and then evaluates the function inside this hypercube; the displacement-shrink stage calculates the displacement and updates the parameters of the hypercube; the searching areas stage using certain rules find the next hypercube. The design stages of the proposed hypercube optimization search (HOS) algorithm are presented. The proposed HOS algorithm is tested on specific benchmark functions. The experimental results on different test functions demonstrate that the HOS algorithm has shown to be a promising approach for finding the solutions of a set of optimization problems.