Digital Commons Network^™

F22rs Sgr No. 2 (Prime Time Class Scheduling), Cooper Ferguson, Emma Long, Calvin Feldt, Elizabeth Laurent

Student Senate Enrolled Legislation

To Urge and Request that the University Registrar halts the reimplementation of a policy that limits departments to scheduling no more than 55% of their course sections within prime-time hours

Reference Staffing And Scheduling Models In Archives And Special Collections: A Survey Analysis Of Prepandemic Practices, Amanda K. Hawk

Faculty Publications

Reference services form the core function of any type of library. Even when faced with shrinking budgets and staff sizes, library and archives workers continue to provide reference services to meet the demands of researchers. Yet a critical analysis of the internal systems used for archival and special collections reference work is lacking compared to the robust body of research about users of collection materials. This article presents findings from a national survey about reference staffing and scheduling models in archival and special collections repositories conducted immediately prior to the onset of the COVID-19 pandemic. The survey data revealed specific …

A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing, Jose Napoleon Martinez

LSU Doctoral Dissertations

In this research, we investigated the application of deep reinforcement learning (DRL) to a common manufacturing scheduling optimization problem, max makespan minimization. In this application, tasks are scheduled to undergo processing in identical processing units (for instance, identical machines, machining centers, or cells). The optimization goal is to assign the jobs to be scheduled to units to minimize the maximum processing time (i.e., makespan) on any unit.

Machine learning methods have the potential to "learn" structures in the distribution of job times that could lead to improved optimization performance and time over traditional optimization methods, as well as to adapt …