ABSTRACT
In genetic algorithm, the variables are assigned to the predefined segments of the genetic string. For example, in Simple Genetic Algorithm (SGA) the genetic string consists of the ordered sequence of the encoded variables and parameters of the problem. Every segment of the genetic string contains useful information. This type of representation works reasonably well for most of the simple optimization problems, which have the number of variables fixed at the outset and unchanging during the evolution. The majority of the current optimization problems belong to this class, described by the following equation: () min f ( x 1 , ⋯ , x N ) https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9780429470134/e855975c-0d74-4d7a-9ce5-4009e993aefc/content/equ7_0001.tif"/>
