Solving university course timetabling problem using localized island model genetic algorithm with dual dynamic migration policy

Alfian A. Gozali, Bobby Kurniawan, Wei Weng, Shigeru Fujimura

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The University Course Timetabling Problem (UCTP) is a scheduling problem of assigning a teaching event in a certain time and room by considering the constraints of university stakeholders such as students, lecturers, and departments. This problem becomes complicated for universities with a large number of students and lecturers. Moreover, several universities are implementing student sectioning, which is a problem of assigning students to classes of a subject while respecting individual student requests, along with additional constraints. Such implementation also implies the complexity of constraints, which is larger accordingly. However, current and generic solvers have failed to meet the scalability and reliability requirements for student sectioning UCTP. In this paper, we introduce the localized island model genetic algorithm with dual dynamic migration policy (DM-LIMGA) to solve student sectioning UCTP. Our research shows that DM-LIMGA can produce a feasible timetable for the student sectioning problem and get better results than previous works and the current UCTP solver. Our proposed solution also consistently yield lower violation number than other algorithms, as evidenced by UCTP benchmark experiment results.

Original languageEnglish
Pages (from-to)389-400
Number of pages12
JournalIEEJ Transactions on Electrical and Electronic Engineering
Volume15
Issue number3
DOIs
Publication statusPublished - 2020 Mar 1

Keywords

  • island model genetic algorithm
  • localization strategy
  • migration policy
  • University course timetabling problem

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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