Modeling and optimal planning for the higher education using control engineering and genetic algorithm

In the last few decades, governments have been allocating considerable resources to plan for their future education systems. To do this, simulation models have been intensively utilized to develop different planning scenarios. Normally, these models are extremely complex and reaching optimum planning scenarios is almost impossible. This paper is trying to introduce more efficient modeling approach that is mainly based engineering control. Also, it introduces a powerful optimization tools namely GA to develop optimal planning scenarios. The results show the ability of the proposed techniques in providing optimal scenarios in an easy fashion when compared with the time consuming manual iteration approach with significant reduction in the government expenditure without sacrificing education quality.