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A Tabu Search-based University Lectures Timetable Scheduling Model

by Adewale O. Sunday, Ibam E. Onwuka, Izundu Kingsley E.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 9
Year of Publication: 2018
Authors: Adewale O. Sunday, Ibam E. Onwuka, Izundu Kingsley E.
10.5120/ijca2018917599

Adewale O. Sunday, Ibam E. Onwuka, Izundu Kingsley E. . A Tabu Search-based University Lectures Timetable Scheduling Model. International Journal of Computer Applications. 181, 9 ( Aug 2018), 16-23. DOI=10.5120/ijca2018917599

@article{ 10.5120/ijca2018917599,
author = { Adewale O. Sunday, Ibam E. Onwuka, Izundu Kingsley E. },
title = { A Tabu Search-based University Lectures Timetable Scheduling Model },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2018 },
volume = { 181 },
number = { 9 },
month = { Aug },
year = { 2018 },
issn = { 0975-8887 },
pages = { 16-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number9/29799-2018917599/ },
doi = { 10.5120/ijca2018917599 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:05:29.056351+05:30
%A Adewale O. Sunday
%A Ibam E. Onwuka
%A Izundu Kingsley E.
%T A Tabu Search-based University Lectures Timetable Scheduling Model
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 9
%P 16-23
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Scheduling University Courses is regarded as a Non-deterministic Polynomial-time hardness (NP-hard) problem. This is because no universal constraint works for all universities. While some will have constraints similar, they might differ in their resource values - length of days, time slots, and rooms. Several literatures have been able to address several constraints, using various optimization methods - genetic algorithms, tabu search and so on. The result often time works but lacks adoptability due to their non-inclusiveness of some resource parameters - day and dynamic time-slot. In this research, we address the various constraints related to the Federal University of Technology Akure (FUTA) using mathematical model that includes the necessary resource parameters. We adopt Tabu search diversification approach to implement a scheduling system that satisfies the constraints defined.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Timetable Tabu Search Constraint Diversification Economy Code Protocol (ECP) Mathematical Model Comfort Adjustment Factor (CAF).

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