Abstract

COVID-19 is rapidly spreading throughout the world’s communities. The terms “physical distance” and “social distancing” are used to emphasize the importance of always remaining at least 6 feet away from others. As universities reopen, it’s more important than ever to enforce the guideline when creating examination schedules with fixed variables like rooms and time slots. Many algorithms have been implemented to successfully schedule University Examination Time Tabling (UETT). This research offers a novel method for upgrading the genetic algorithm with tabu list memory. The proposed approach achieved results that reduce student crowding compared to the standard approach, with less than 50% of the actual university capacity over time slots. The quantitative results proved that the use of this Approach will reduce the risk of crowding during university exams, at university campus.