The problem of developing a class schedule for a faculty has been proven to be NP-complete. Therefore when the schedule is large enough, finding just one feasible solution can be impossible for any direct search algorithm within a reasonable time. This project is geared toward investigating the possibility of using genetic-based algorithms to solve faculty scheduling problems of 100 courses or larger quickly. Multiple versions of genetic algorithms and heuristics are tested. Many parameter levels for these algorithms are optimized for fastest convergence.
Department, Program, or Center
Computer Science (GCCIS)
Soule, Kevin, "Faculty scheduling using genetic algorithms" (2006). Thesis. Rochester Institute of Technology. Accessed from
RIT – Main Campus
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