TY - JOUR
T1 - Reinforced island model genetic algorithm to solve university course timetabling
AU - Gozali, Alfian Akbar
AU - Fujimura, Shigeru
N1 - Funding Information:
Indonesia Endowment Fund for Education (LPDP), a scholarship from Ministry of Finance, Republic of Indonesia, supports this work. We conduct this research while at Graduate School of Information, Production, and Systems, Waseda University, Japan.
Publisher Copyright:
© 2018 Universitas Ahmad Dahlan.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - The University Course Timetabling Problem (UCTP) is a scheduling problem of assigning teaching event in certain time and room by considering the constraints of university stakeholders such as students, lecturers, departments, etc. This problem becomes complicated for universities which have immense number of students and lecturers. Therefore, a scalable and reliable timetabling solver is needed. However, current solvers and generic solution failed to meet several specific UCTP. Moreover, some universities implement student sectioning problem with individual student specific constraints. This research introduces the Reinforced Asynchronous Island Model Genetic Algorithm (RIMGA) to optimize the resource usage of the computer. RIMGA will configure the slave that has completed its process to helping other machines that have yet to complete theirs. This research shows that RIMGA not only improves time performance in the computational execution process, it also offers greater opportunity to escape the local optimum trap than previous model.
AB - The University Course Timetabling Problem (UCTP) is a scheduling problem of assigning teaching event in certain time and room by considering the constraints of university stakeholders such as students, lecturers, departments, etc. This problem becomes complicated for universities which have immense number of students and lecturers. Therefore, a scalable and reliable timetabling solver is needed. However, current solvers and generic solution failed to meet several specific UCTP. Moreover, some universities implement student sectioning problem with individual student specific constraints. This research introduces the Reinforced Asynchronous Island Model Genetic Algorithm (RIMGA) to optimize the resource usage of the computer. RIMGA will configure the slave that has completed its process to helping other machines that have yet to complete theirs. This research shows that RIMGA not only improves time performance in the computational execution process, it also offers greater opportunity to escape the local optimum trap than previous model.
KW - Genetic algorithm
KW - Island model
KW - University course timetabling problem
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U2 - 10.12928/TELKOMNIKA.v16i6.9691
DO - 10.12928/TELKOMNIKA.v16i6.9691
M3 - Article
AN - SCOPUS:85064715363
SN - 1693-6930
VL - 16
SP - 2747
EP - 2755
JO - Telkomnika (Telecommunication Computing Electronics and Control)
JF - Telkomnika (Telecommunication Computing Electronics and Control)
IS - 6
ER -