The above methods and techniques were implemented and validated using real-world data, and the results were found to be highly effective, accurately quantifying the workload in a variety of scenarios, and allocating lectures, tutorials, and labs to faculty members while minimizing fragmentation and uneven faculty overloading. The entire teaching workload allocation process involving 1152 lectures, tutorials, and labs took only 30 seconds on a standard PC. Finally, the proposed techniques ensure an inclusive approach by incorporating the preferences of students, faculty, and management while ensuring an equitable proportion of lectures, tutorials, and labs for each faculty member. vi