Date of Graduation
Bachelor of Science in Industrial Engineering
University degree plans must be carefully planned so that they allow students the best chance of succeeding. Although for the better, with the advancement of technology and its incorporation into the classroom, it can be argued that the complexity and difficulty of some long-established engineering core classes has changed. With this trend certain combinations of engineering courses have become unfavorable in terms of course withdrawal and fail rates stemming from the interaction of course challenges. A wealth of data has been collected on this topic and will be utilized in this project. As one can imagine, the probability of success in a student completing a degree has infinitely many variables. One area this complex problem can be simplified is modeling the degree curriculum as an Activity-on-Node Network, a long-established fundamental engineering model. Courses are represented as nodes in the network, and the flow is restricted by precursors and successors, thus representing pre- and co-requisite relationships. With the knowledge of experimental failure probabilities in certain courses, individual student grade reports, and established pre-requisite constraints, this project aims to apply modern optimization tools to university curricula in hopes that the best solution can be obtained to maximize the probability of success.
networks, graph theory, shortest path problem, optimization, network optimization
Rhomberg, C. (2020). Curriculum Optimization via Activity-on-Node Network Modeling. Industrial Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/ineguht/67
Engineering Education Commons, Industrial Engineering Commons, Operational Research Commons, Other Operations Research, Systems Engineering and Industrial Engineering Commons, Systems Engineering Commons