In this project, I have used Genetic Algorithms for the Classification of Employees in the Context of a Transformation to the e-Administration in C++.
This program presents a general vision to perform a transformation of ordinary service to an e-service as part of the modernization of a public Administration. Human resources have been opted to play an essential role in this transformation. This code is summed up in a method that helps to choose employees (functionaries) most willing to be adapted to the changes induced by the establishment of an e-service. The genetic algorithms have been chosen to be applied, on the basis of criteria retained in the evaluation of employees, in order to create mutations between generations to reach a better generation. In this way, we choose the fittest population for this service. In this project, the major interest is in the selection of employees, pre-disposed to changes and who can easily integrate tools and services of the e-Governance into their missions. For this, the principles of the genetic algorithm have been chosen to be applied to a restricted population (40 employees) and with only five subcategories. The basic idea of this work resides in an application field of genetic algorithms around the retraining of employees and especially officials in the transformation of administrative services around the implementation of solutions-oriented to the e-Governance. To find the most able employees to cope with the change, three intermediate generations were through before arriving at the best generation. These intermediate generations are composed of individuals having more adapted profiles. This work is part of a most complex approach that aims to expand the study to a more representative population (hundreds) considering all of the above categories criteria. It may also apply the fuzzy logic to quantify the degrees of importance of the different subcategories and the different categories with respect to the employee profile. The expected objective is the establishment of a tool, following a diagnosis, which allows to classify employees and to take a decision for any assignment or for any training to follow. This process can be used also to evaluate employees in their career plans.