Optimization of the Room Booking Processes in a Nonprofit Organization
Abstract
Room allocation is a combinatorial optimization problem commonly encountered in profit-driven settings, where the goal is to maximize revenue through efficient scheduling. In contrast, this study focuses on nonprofit organizations, where the primary goal is to optimize resource utilization and improve service delivery. Specifically, the study examines a nonprofit organization with multiple branches. Due to the branches having different processes and different teams for the same tasks, the organization faces various operational challenges. To address these challenges, two building-level mathematical models are developed. The first model, based on first-come-first-served (FCFS) logic, provides next-best booking suggestions to human decision-makers, reducing response times from 72 hours to under a minute. A constraint removal heuristic is created to relax conflicting rules when necessary to accommodate more customers. The second model, called Long-Term Planning (LTP), generates final schedules by collecting customer data at regular intervals. It offers two decision frameworks: a reactive approach that adapts the schedule on customer basis throughout the planning horizon, and a traditional method that finalizes assignments at once.
Keywords: Decision support systems, mixed-integer programming, nonprofit optimization, optimization, room allocation, room booking