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Using Random Scheduling Technique with Crowd-Sourcing to Solve Exam Timetable

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2022
Charles Roland Haruna, Elliot Attipoe, Isaac Armah Mensah, Kwame Opuni-Boachie Obour Agyekum

Charles Roland Haruna, Elliot Attipoe, Isaac Armah Mensah and Kwame Opuni-Boachie Obour Agyekum. Using Random Scheduling Technique with Crowd-Sourcing to Solve Exam Timetable. International Journal of Computer Applications 183(50):1-7, February 2022. BibTeX

	author = {Charles Roland Haruna and Elliot Attipoe and Isaac Armah Mensah and Kwame Opuni-Boachie Obour Agyekum},
	title = {Using Random Scheduling Technique with Crowd-Sourcing to Solve Exam Timetable},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2022},
	volume = {183},
	number = {50},
	month = {Feb},
	year = {2022},
	issn = {0975-8887},
	pages = {1-7},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2022921928},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


An examination timetable is arranging temporary, a set of meetings making sure that all given constraints are fulfilled. A university has many colleges, faculties and programs within departments, each having their plan about how, when and where their examination should be run. Students can offer courses from a combination of several programs in the same or different departments, from different faculties and or colleges. Thus, scheduling of an examination timetable is a large and complex assignment. Various university examination timetabling systems have been proposed and developed, but not all university examination timetables can be scheduled by machines only, for example in the case of the University of Cape Coast. Both machine and experts are required. In this paper, a case study is presented and a hybrid technique tailored to suit the University of Cape Coast examination timetable scheduling is proposed, where machines are first used then experts complete the scheduling. Real data set from the University is used in this research and the effectiveness of the proposed technique is presented by performing multiple experiments and the results of an examination timetable using real data sets from past academic years (semesters) from the University of Cape Coast are discussed.


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Timetabling Problem, Examination Timetabling Scheduling, Random Scheduling Algorithm, Crowd-Sourcing