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dc.contributor.authorYu, Zhe-
dc.description.abstractExamination scheduling has been a hard problem highlighted in most post-secondary institutions due to its complexity and limitation, and it may take overwhelming time and effort for educational administrators to organize a satisfactory exam timetable with trial and error. Traditional techniques such as graph-based heuristics could not always guarantee an optimal solution, and constraint-based methods, i.e., mixed linear programming (MLP), however, are usually computationally intensive and may need human intelligence involved during the scheduling process. Role-Based Collaboration (RBC) methodology is found to be an innovative theory to tackle such examination scheduling issues. It enables us to comprehensively capture miscellaneous constraints in extended integer linear programming (x-ILP) expressions in correspondence with its Environments - Classes, Agents, Roles, Groups, and Objects (E-CARGO) model as well as the sub-pattern, i.e., Group Role Assignment plus Constraints (GRA+). A feasible optimization solution is proposed in this research to deal with such well-formalized models with the technical support of IBM ILOG CPLEX R , an advanced optimizer that is verified to be significantly superior against other optimizing approaches in terms of both efficiency and accuracy. By means of considerable case studies, the results convince us that our approach to examination scheduling is capable of obtaining optimal solutions respecting multiple constraints in less computational time, and thus this research is believed to have significant contributions to post-secondary practice.en_US
dc.subjectExamination schedulingen_US
dc.subjectexam timetableen_US
dc.subjectJava applicationen_US
dc.subjectbenchmark datasetsen_US
dc.titleA new approach to examination scheduling with allowable constraints for post-secondary institutions using GRA+en_US
dc.description.degreeMaster of Science (M.Sc.) in Computational Sciencesen_US
dc.publisher.grantorLaurentian University of Sudburyen_US
Appears in Collections:Computational Sciences - Master's theses
Master's Theses

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