A transdisciplinary approach to course timetabling an optimal comprehensive campus application

Abstract

Academic timetabling is a core process of higher education institutions (HEIs) with profound implications for stakeholder satisfaction and organizational efficiency. This process serves as the operational backbone of every HEI. It involves the allocation of professors to course-sections, schedules, and facilities such as classrooms and laboratories for a specific academic term. Given its mathematical complexity (NP-Hard) and despite the extensive literature on timetabling practices, real-world applications often present challenges that deviate from standard problem formulations, creating a gap between theory and practice. This research addresses these challenges by promoting knowledge integration and improving decision-making processes. The contribution of this article is twofold: Firstly, it introduces a transdisciplinary framework that considers stakeholder preferences and available organizational resources to optimize the expected academic performance of HEIs. At the core of this framework lies a quantitative decision support tool (based on a mixed integer optimization model) designed to bridge knowledge and resource gaps, thus aiding the decision-making team in achieving their objectives. Secondly, the article presents a practical demonstration of this framework using data from an entire HEI Campus, encompassing all schools and academic programs, to illustrate its efficiency and benefits.