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.
Highlights
Comparing two numbers with each other is not difficult and cannot be processed by any special method [1]
This methodology was applied to compare the effects of various changes of algorithms on the efficiency of the genetic algorithm of global optimization [4, 5] and the collective optimization method based on common bionic algorithms - Co-Operation of Biology Related Algorithms (COBRA) [6]
This technique made it possible to compare the values of the genetic optimization algorithm parameters and the collective optimization method based on common bionic algorithms - the CoOperation of Biology Related Algorithms (COBRA), at a significance level of 0.05
Summary
Comparing two numbers with each other is not difficult and cannot be processed by any special method [1]. The comparison of two variational series of numbers is reduced to a simple comparison of two numbers Such a simple comparison can be carried out for an unlimited number of rows depending on the problem being solved. Such a simple comparison has very weak mathematical power and is not suitable for serious research. [2, 3] With such experimentation, we would always like to have a tool - a technique with which one could make the correct and most accurate comparison of changes made to algorithms To solve this question, I created a method for comparing variational series, i.e. methodology for comparing the effect of changes on the efficiency of optimization algorithms. A new method of variational series comparison was developed and applied
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