Optimization of a multi-objective university course timetabling problem with a hy-brid WOA&NSGA-II (Case study: IAU, Robat Karim branch)

Scheduling and timetabling for university system have been a source of attention and an important challenge for the people in charge of administrations. the regulations and infrastructures are very diverse between universities, making it impossible to come up with a universal model for all. we, in this research, focused on coming up with an algorithm to help with timetabling of class courses for islamic azad university of robat karim. our goal was to define an algorithm that could improve teacher satisfaction, and overall efficiency of the university timetabling. instead, we managed to come up with an efficient algorithm. this research considers different factors such as teacher satisfaction, knowledge and skillset, categorizes students based on un-dergraduate versus post graduate degree, their research background, their scores and finally student satisfaction as well. this multi-objective mathematic model accounts for all the rules, regulations, and limitations of the university setting while following challenging confinements that guarantee the feasibility of the solution. using metaheuristic algorithm of whale and genetic, while avoiding any breach of the soft limitations, we managed to come up with a system that provides the most satisfaction between the teachers and students. in our research, we compared whale and genetic algorithm with 4 other metaheuristic algo-rithms. we concluded that the results of whale and genetic algorithm are superior to other algorithms in regards to: improved function goals, less run time, more pareto front averages, more efficient solutions and results.