University Course Scheduling Optimization under Uncertainty based on a Probability Model

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University Course Scheduling Optimization under Uncertainty based on a Probability Model

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Publication Bachelor thesis
Title University Course Scheduling Optimization under Uncertainty based on a Probability Model
Author Sandh, David ; Knutsäter, Lucas
Date 2019
English abstract
In this thesis, we present a way to model uncertainty when optimizing the University Timetabling Problem. It is an NP-hard, combinatorial and highly constrained problem. In this thesis, we first propose a standardized model based on the data from Malmö University. Then, we propose our extended model, which, during the creation of the solution, accounts for the probability of unexpected events to occur and changes the solution accordingly. To implement our model, we use a Particle Swarm Optimization (PSO) algorithm. In our experiments, we find problems with the algorithm converging too early. We analyze the performance of our extended model compared to the standardized model, using a benchmark devised by us, and find that it performs well, reducing the number of constraint violations by 32%. We then suggest further areas of research in regards to this uncertainty model.
Publisher Malmö universitet/Teknik och samhälle
Language eng (iso)
Subject University Timetabling
Timetabling
Optimization
Uncertainty
Evolutionary algorithms
Handle http://hdl.handle.net/2043/29167 Permalink to this page
Link to publication in DiVA Find this research publication in DiVA (n/a for student publ.)
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