Setting of Control Parameters of SOMA on the Base of Statistics

Abstract

Evolutionary techniques are generally considered to be effective tool for solving a wide range of optimization problems. However, those algorithms are controlled by a special set of parameters according to their type. Control parameters of self-organizing migrating algorithm (SOMA) can be divided into several groups: the stopping parameters, parameters which depended on the type of problem to be solved and finally, parameters that are responsible for the quality of the results. The values of some parameters are directly evident from the nature of the algorithm, but the values of some may vary based on the problem and their efficient settings may significantly affect the quality of the calculation. This chapter focuses on the possibility of using some statistical methods to determine the effective values of some parameters of SOMA. The use of statistical methods is elucidated by an illustrative example.