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Intelligent based Multi-Agent Approach for University Timetable Scheduling System

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Nicholas Oluwole Ogini, Noah Oghenefego Ogwara, Obeten Obi Ekabua

Nicholas Oluwole Ogini, Noah Oghenefego Ogwara and Obeten Obi Ekabua. Intelligent based Multi-Agent Approach for University Timetable Scheduling System. International Journal of Computer Applications 182(1):10-21, July 2018. BibTeX

	author = {Nicholas Oluwole Ogini and Noah Oghenefego Ogwara and Obeten Obi Ekabua},
	title = {Intelligent based Multi-Agent Approach for University Timetable Scheduling System},
	journal = {International Journal of Computer Applications},
	issue_date = {July 2018},
	volume = {182},
	number = {1},
	month = {Jul},
	year = {2018},
	issn = {0975-8887},
	pages = {10-21},
	numpages = {12},
	url = {},
	doi = {10.5120/ijca2018917432},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


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 by adopting the object oriented analysis and design methodology approach.


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