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Optimizing processes is essential to reduce costs, improve product quality and ensure the sustainability of organizations. This research proposes a support system to automate the assignment of the teaching load of an educational unit, maximizing teacher satisfaction with the assigned subjects, reducing administrative times and increasing the process transparency. [1] [2] guidelines were followed, applying the integer linear programming model, using Excel and R programs to solve the mathematical problem. The findings show that 84% of teachers will have maximum satisfaction in assigned subjects, and the rest reach 80% satisfaction. Additionally, 92% of the subjects were designated to teachers with maximum experience, knowledge and preference for them, for the remaining 8% the satisfaction range was between 80-93%, which will benefit the teaching act.

With the development of technology, easy access to it and the pressures of today's world, conditions are created in which people may be tempted to commit digital frauds It is important that educational institutions encourage the students aware of the use of social networks in a licit manner and the importance of technology in the development of the individual competitiveness and organizational. This research addresses the implementation of teaching-learning strategies aimed at reinforcing academically honest behavior during virtual activities and empowering students with their own knowledge. Through the teaching interventions it was possible to reduce the illicit interactions of the students during the evaluations by 26% and increase the student performance to 84%.

This research considers the management of the formation of collaborative groups to work virtually in the development of a task, considering the academic performance, the resilience and the aptitude to the technology, then, it is a multi-objective optimization. The descriptive study and based on the theories of social construction of knowledge and approximate sets, proposes the design of a genetic algorithm to establish intra-heterogeneous and inter-homogeneous teams according to the specified restrictions. The development of the proposal made it feasible to codify the students, define the genetic selection, crossing and mutation operators, which can lead to the best solution, after successive iterations and within the previously defined evaluation parameters.