Multiple-hybrid case-based reasoning approach for university course timetabling problem

The University Time Tabling problem (UCTP) is an allocation process to schedule courses with available time slots for suitable lecture halls, classes or rooms in every semester. The academic time tables design has become a very complex issue and difficult task as such it is classified as NP-hard problem. The objectives of this paper is to achieve higher accuracy for time tabling plotting as well as improve the effectiveness while generating academic courses time tables. With the aim to improve timetabling solution, we investigate into a new algorithm which is based on Case-based Reasoning (CBR) retrieval function. The idea proposed is known as Human Preference Adaptable Retrieval Approach – HPARA and is separated in three parts, with the combination of different functionality: Prioritized Attributes, Frequency Grouping, and Value Difference Measurement. The CBR retrieval is a strategy to retrieve similar cases from previous time tabling for generating new time tables. Retrieved cases will then filtered with the according functionality: Prioritized Attributes, Frequency Grouping, and Value Difference Measurement too seek for the most suitable components. The proposed CBR algorithm is tested with the database of Faculty of Computer Science and Information Technology for the past five years compared with Genetic Algorithm (GA). Experimental results show promising improvement for both accuracy and effectiveness with the proposed CBR algorithm to generate UCTP