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Multiple case-based retrieval for university course timetabling problem


Hong, Siaw Theng (2016) Multiple case-based retrieval for university course timetabling problem. Masters thesis, Universiti Putra Malaysia.


This thesis presents research for Case-based reasoning (CBR), a knowledge-based reasoning technique to solve university timetabling problem such as resource allocation for student’s course timetabling. CBR model’s was reviewed on Case-based Retrieval for timetabling discloses improvement that can be done to excel in accuracy and time consuming. From the review of past case-based retrieval techniques, a few concern is being investigate for the cases retrieval process such as the effectiveness of retrieval and time required to generate a comprehensive timetable. This research is aim to optimize the effectiveness of retrieval as well as generate a timetable in the shortest time possible with minimize violation. The case-based retrieval technique is further enhanced and improvised into a new algorithm known as Multiple Case-based Retrieval. The algorithm is combining separated distinct processes, with the combination of different functionalities: Prioritized Attributes, Frequency Grouping, and Value Difference Measurement. The algorithm was running on timetabling tests, comparing to classic Case-based retrieval and Genetic Algorithm for a wider comparison. Graphs are plot according to the readings from timetabling tests to show the result comparisons. Results from the experiments show the effectiveness and elapsed time to generate a timetable. Multiple Case-based Retrieval shows promising results in improving the effectiveness of case-based retrieval and also reduced the time required to generate a new timetable. This research summarize that the algorithm in retrieval is playing a very important role for an effective timetabling generator. Future research may concern to improve of the process of retaining cases, focus on case-based handling storage for generated cases for future review.

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Additional Metadata

Item Type: Thesis (Masters)
Subject: Universities and colleges - Management
Subject: Scheduling - Data processing
Call Number: FSKTM 2016 38
Chairman Supervisor: Abu Bakar Md Sultan, PhD
Divisions: Faculty of Computer Science and Information Technology
Depositing User: Ms. Nur Faseha Mohd Kadim
Date Deposited: 10 Jul 2019 01:12
Last Modified: 10 Jul 2019 01:12
URI: http://psasir.upm.edu.my/id/eprint/69369
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