| Abstrakt: |
The iteration history curve of optimization algorithms is a saturation-type development curve or sigmoid shape curve. After an overview of several different sigmoid curves, the iteration history curve of the RVA (Random Virus Algorithm) is analysed in order to find its best settings for a given optimization problem. The analysis of the characteristics and numerical parameters of the iteration history curve provides the possibility to discover the speed and efficiency of the algorithm without the necessity to wait throughout the whole running until its final result, which can speed up numerical experiments during the search for the solution to the optimization problem and while 'fine tuning' the algorithm to the given task. Since sigmoid-type curves can be found in many different fields of life (the history of the sport world records, comparison of the achievements of several groups), the results of this analysis can be used in several different domains of life, when the ranking, comparison, evaluation or qualification of several individuals or groups is important. [ABSTRACT FROM AUTHOR] |
