An Evaluation of the Great Deluge Algorithm in Course Timetabling : As Applied to the KTH-Inspired University Course Timetabling Problem

• Main Authors: Chammas, Kristoffer, Sirak, Simon
• Format: Others
• Language: English
• Published: KTH, Skolan för elektroteknik och datavetenskap (EECS) 2019
• Subjects: Computer and Information Sciences; Data- och informationsvetenskap
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259907

The University Course Timetabling Problem (UCTP) can be loosely described as assigning events (e.g lectures) to rooms and timeslots in a way that results in a feasible timetable that is optimal according to some custom criteria. The problem has become increasingly relevant as more programs become available in universities. Due to the complexity of UCTP, the problem is usually solved approximately using heuristics. The KTH-inspired UCTP is a variant of the UCTP that is adapted to KTH Royal Institute of Technology. However, few heuristics have been implemented for this variant of UCTP. Therefore, this study introduces an implementation of The Great Deluge heuristic to the KTH-inspired UCTP, and compares it to a state-of-the-art solver for KTH-inspired UCTP. The Great Deluge implementation was compared against the state-of-the-art KTH-inspired UCTP solver for different time limits. For each time limit, the output timetable quality was recorded over several executions. The comparison was done on two problem instances of varying complexity. The results suggest a behavior that varies over time. For larger time limits, GD produced better timetables than the state-of-the-art and the overall quality of timetables was consistent over several executions. For smaller time limits, GD produced worse timetables than the state-of-the-art and the overall quality of timetables was inconsistent over several executions. A few potential causes for the improved performance during the later stages of execution were found through further analysis of the results. Perhaps the biggest potential cause was utilizing the greedy behavior obtained during the mid to late stages of execution. === ”The University Course Timetabling Problem” (UCTP) handlar i grova drag om att, baserat på ett antal kriterier, schemalägga föreläsningar, övningar och laborationer på ett optimalt sätt. Problemets relevans har ökat allt eftersom universitet utökar sina programutbud. På grund av komplexiteten hos UCTP löses problemet vanligtvis approximativt med hjälp av heuristiker. ”KTH-inspired UCTP” är en KTH-anpassad variant av UCTP för vilken endast ett fåtal heuristiker har implementerats. Denna variant har exempelvis inte lösts av en vanlig heuristik inom UCTP, ”The Great Deluge” (GD). Denna studie fokuserar därför på att applicera GD på ”KTH-inspired UCTP” och jämföra denna med äldre implementationer, med fokus på den bästa tillgängliga implementationen. GD-implementationen jämförs med den bästa tillgängliga implementationen för ”KTH-inspired UCTP” för olika tidsgränser. Kvaliteten hos de resulterande schemana evalueras och sparas sedan över flera körningar. Jämförelsen gjordes på två probleminstanser av olika komplexitet. Resultatet av jämförelsen föreslår att GD producerade bättre scheman för högre tidsgränser men sämre scheman för lägre tidsgränser. Vidare analys föreslår att denna förbättring beror på utnyttjandet av det giriga beteendet som vår GD-implementation uppvisar vid senare delar av exekvering.