Browsing Theses and Dissertations (MU) by Thesis Department "Industrial Engineering (MU)"
Now showing items 1-6 of 6
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AI-driven techniques for enhanced efficiency in psychiatry clinical scheduling
(University of Missouri--Columbia, 2023)[EMBARGOED UNTIL 12/1/2024] In recent times, psychiatry clinics are constantly facing late patient arrivals. Patient unpunctuality significantly affects the use of resources and patient waiting times, among other quality ... -
Assessing strategies for achieving environmentally sustainable food systems using robust optimization
(University of Missouri--Columbia, 2023)[EMBARGOED UNTIL 5/1/2024] With growing populations and affluence, many organizations predict that food demand will increase, which presents considerable challenges to achieving economic, environmental, and social ... -
Collaborative human-robot order picking system : algorithms for task allocation and routing in complex environments
(University of Missouri--Columbia, 2023)[EMBARGOED UNTIL 8/1/2024] Order picking, which involves retrieving items from storage locations for an internal or external customer, is a core function in warehouses and accounts for up to 65 percent of the total operating ... -
Material and volunteer convergence in developing a disaster resource portfolio
(University of Missouri--Columbia, 2023)[EMBARGOED UNTIL 5/1/2024] Disaster relief operations have been conducted by humanitarian agencies for decades, yet the problem of material and volunteer convergence still exists today. The massive influx of unsolicited ... -
Predicting student performance in an augmented reality learning environment using eye-tracking data
(University of Missouri--Columbia, 2023)This paper investigates the use of eye-tracking data as a predictor of student performance in an augmented reality (AR) learning environment. 33 undergraduate students enrolled in an ergonomics course at the University of ... -
A rare event classification in the advanced manufacturing system: focused on imbalanced datasets
(University of Missouri--Columbia, 2022)In many industrial applications, classification tasks are often associated with imbalanced class labels in training datasets. Imbalanced datasets can severely affect the accuracy of class predictions, and thus they need ...