Guided Genetic Algorithm to Solve University Course Timetabling with Dynamic Time Slot

Fachrie, Muhammad and Waluyo, Anita Fira (2020) Guided Genetic Algorithm to Solve University Course Timetabling with Dynamic Time Slot. In: 2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), Yogyakarta., https://ieeexplore.ieee.org/document/9315448.

	Text Artikel ISRITI 2021 - Fachrie&Anita.pdf Download (340kB)
	Text 5. Similarity, Fachrie-Anita, Guided Genetic Algorithm.pdf Download (1MB)
	Text Peer Review-Guided Genetic Algorithm.pdf Download (392kB)

Abstract

This paper discusses about one of the most popular technique in Evolutionary Computation, i.e., Genetic Algorithm to solve the UCTP that has dynamic teaching time slot. Duration of a lecture is determined by the course’s credit which means that the structure of course timetable can be different between one day to the others. This kind of timetable structure is more complex since the flexible time slot could produce high number of schedules possibility. Hence, a flexible chromosome is developed to deal with dynamic time slot and enhanced the efficiency of the system by eliminating the crossover process which usually time consumed. A Guided Creep Mutation is proposed to act as an evolutionary operator that guides the chromosomes to find global optimum by changing certain gene value gradually in every generation. Our system successfully generated optimum schedule for 878 and 1140 courses in odd and even semester with zero collision in rooms, time, lecturers, also satisfied all soft constraints given. Based on our experiments, the system needs relatively small number of generations with few chromosomes to generate an optimum schedule. Keywords— course timetabling, genetic algorithms, combinatorial optimization, evolutionary computation, dynamic time slot

Item Type:	Other
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User:	Mrs. Anita Fira
Date Deposited:	22 Feb 2024 14:30
Last Modified:	09 Mar 2024 03:04
URI:	http://eprints.uty.ac.id/id/eprint/14871

Actions (login required)

View Item