Analysis of The Effect of Random Number Range on The Process of Selecting Chromosomes in Genetic and Memetic Algorithm for Query Optimization

Abstract

Imization of query processing needs to be done so that the system can be utilized optimally, and the processing time can be minimized. Genetic algorithms (GA) and memetic algorithms (MA) are alternative algorithms that can be used to perform query optimization. MA is an extension of genetic algorithms combined with local search techniques. An important part of GA and MA-as an extension of GA is the selection process to determine the best chromosome. In this selection process, there is a parameter that determines chromosome selection, namely the random number. From the results, it was found that query optimization was influenced by the range of random numbers applied to the chromosome selection process. The greater the random number range, the more it increases performance (optimization) in accelerating query execution time. The distribution of query execution time with a larger random number range is relatively more homogeneous (stable) than the distribution of query execution time values with a smaller random number range.