New method of COBRA parameters comparison

Abstract

Abstract The comparison between two or more number rows is very difficult and impossible to perform without additional mathematical processing and formulas. A tool is needed to determine whether the efficiency of the algorithm has significantly improved, the changes made, or at a certain level of significance, these changes have not made any special improvements to the operation of the optimization algorithm. The methods of variational series comparison were analyzed. A new method of variational series comparison was developed. The methodology was tested when choosing parameters and for comparing the influence of initialization methods on the global optimization genetic algorithm and the collective optimization method based on the Co-Operation of Biology Related Algorithms (COBRA) based on bionic algorithms. The studies showed that the new method of variational series comparison well fulfilled its functions and coped with its task.