A Neutrosophic Octagonal Fuzzy Approach for Faculty-Course Assignment in Educational Institutions under Uncertain Preferences and Constraints

Abstract

Educational organizations  are often faced with difficult problems of assigning faculty members optimally to courses, where course preferences, levels of expertise, and constraints of the institution are not known with certainty. In this work, a new neutrosophic octagonal fuzzy approach is presented to tackle the faculty-course assignment problem under uncertainty. The proposed methodology integrates neutrosophic set theory and octagonal fuzzy numbers to simultaneously handle truth, uncertainty, and falsehood to build a complete system for decision making under uncertainty. We develop a mathematical model using real time data from a computer science department of 15 faculty members and 20 courses to include faculty preferences, expertise levels, workload constraints and course requirements. The results show that the neutrosophic octagonal fuzzy method has a success rate of 100% in the course assignment with an average neutrosophic score of 0.8828. The method can effectively deal with uncertainty and incomplete information of educational scheduling problems