Application of Representation and Fitness Method of Genetic Algorithm for Class Scheduling System
Freddie Rick E. Labuanan1, Sheena-Jean E. Tapaoan2, Ricardo Q. Camungao3
1Freddie Rick E. Labuanan, College of Computing, Studies in Information and Communication Technology, Isabela State University – Main Campus, Ramon, Isabela, Philippines.
2Sheena-Jean E. Tapaoan, College of Computing, Studies in Information and Communication Technology, Isabela State University – Main Campus, Echague, Isabela, Philippines.
3Ricardo Q. Camungao, College of Computing, Studies in Information and Communication Technology, Isabela State University – Main Campus, Echague, Isabela, Philippines.
Manuscript received on 14 March 2019 | Revised Manuscript received on 18 March 2019 | Manuscript published on 30 July 2019 | PP: 1816-1821 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1026078219/19©BEIESP | DOI: 10.35940/ijrte.B1026.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper introduced aimed to solve the poor management of schedule, one of the major problems at Isabela State University-Main Campus. Scheduling is a process conducted before a certain event would be executed. The study used and adopt the Representation and Fitness Methods of Genetic Algorithm to formulate a solution. The study showed that the adaptation of the two methods is well fitted for use in solving the stated problem. The representation method creates and generates the pre-scheduling template to be used for the plotting of schedules, and fitness method is how the pre-scheduling template generated and created. The researchers used some criterion of ISO 9126 Standard as an instrument to determine its functionality and usability. Results showed that the representation and fitness methods of the genetic algorithm make the scheduling process more accurate and reliable schedules, lessen the time-consumed and lessen the time-conflicts in the plotted schedules. For future studies to be conducted reformulation of fitness function to include the other components and variables of scheduling like individual schedules for both regular and irregular student and campus extension integration and considering the other indicator of the instrument used are significantly suggested.
Index Terms: Representation, Fitness, Genetic Algorithm, Class Scheduling Algorithm
Scope of the Article: Algorithm Engineering