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Reseach Article

Intelligent based Multi-Agent Approach for University Timetable Scheduling System

by Nicholas Oluwole Ogini, Noah Oghenefego Ogwara, Obeten Obi Ekabua
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 1
Year of Publication: 2018
Authors: Nicholas Oluwole Ogini, Noah Oghenefego Ogwara, Obeten Obi Ekabua
10.5120/ijca2018917432

Nicholas Oluwole Ogini, Noah Oghenefego Ogwara, Obeten Obi Ekabua . Intelligent based Multi-Agent Approach for University Timetable Scheduling System. International Journal of Computer Applications. 182, 1 ( Jul 2018), 10-21. DOI=10.5120/ijca2018917432

@article{ 10.5120/ijca2018917432,
author = { Nicholas Oluwole Ogini, Noah Oghenefego Ogwara, Obeten Obi Ekabua },
title = { Intelligent based Multi-Agent Approach for University Timetable Scheduling System },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2018 },
volume = { 182 },
number = { 1 },
month = { Jul },
year = { 2018 },
issn = { 0975-8887 },
pages = { 10-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number1/29724-2018917432/ },
doi = { 10.5120/ijca2018917432 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:10:04.548390+05:30
%A Nicholas Oluwole Ogini
%A Noah Oghenefego Ogwara
%A Obeten Obi Ekabua
%T Intelligent based Multi-Agent Approach for University Timetable Scheduling System
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 1
%P 10-21
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Consequently, in this paper, timetabling problem usually leads to conflicts of interest and requires both compromise and cooperation from the participant involved to solve this problem. The proposed system uses three agents: agent 1, 2 and 3 to negotiate the scheduling of courses for both lecture and examination time table. Each agent negotiates for resources according to class size and venue capacity during time tabling generation. This combinatorial problem is both NP-hard and NP-Complete. Previous researches concentrates in solving the problem using genetic algorithm (GA), Artificial Intelligence (AI) and meta-heuristic. The solutions provided are domain specific and the approach adopted in this paper, is through the use of intelligent based multi-agent system which satisfies both hard and soft constraints by improving the time and space efficiency. The system implementation uses Visual BASIC.net by adopting the object oriented analysis and design methodology approach.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Intelligent system time efficiency multi agents timetable scheduling NP-Hard Problem NP-Hard Complete.