Implementation of a genetic algorithm in JavaScript to solve the problem of assigning teachers by academic semester at the Yavirac Higher Technological Institute
Abstract
The allocation of teachers who are going to teach a subject in an academic period is a common problem in higher education institutions. This problem has already been solved using different techniques. I am presenting a solution of a web application applying a genetic algorithm in the backend. IST Yavirac has no administrative staff, and carries out this activity with its teaching staff, who must combine their teaching activities with this administrative activity. Due to the number of variables and their complexity, the problem of assigning teachers per semester is NP-complete; that is, there is no single solution, but rather a set of valid solutions. Artificial Intelligence was chosen to solve this problem, specifically through the design and implementation of a genetic algorithm. This solution is implemented on a REST API web on a Web server with NodeJS and can be implemented in the cloud for production. This article shows the approach used to provide a practical solution, supported by ontologies to represent business objects on chromosomes, instead of the classical representation based on character strings. This approach allows viable solutions to be calculated, which can be accepted by the users. The calculation takes only a few minutes compared to the manual solution that can require up to five working days.
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