GENERATING UNIVERSITY COURSE TIMETABLE USING CONSTRUCTIVE MODELING
DOI:
https://doi.org/10.15588/1607-3274-2019-3-17Keywords:
Timetabling, constructor, genetic algorithm, modelingAbstract
Context. Generating university course timetable is one of the most important tasks of managing the educational process. Growingrequirements for the quality of education, a reduction in the material base and an increase in the number of specialties lead to the
need to optimize the process of using human resources, the classroom fund and to save energy resources. Since all the factors influencing
the schedule are almost impossible to take into account and the interests of the participants in the educational process are diverse,
the task of creating a schedule is multicriteria with a fuzzy set of factors. In this regard, the problem of automating the timetabling
is still one of the urgent problems of the organization of the educational process.
Objective. The goal of the work is the improving the quality of university timetables and reducing the time it takes. The quality
of the schedule is determined by the extent to which the necessary and desirable requirements are met. It is necessary to provide possibility
of expanding the desired requirements without changing the optimizing mechanism.
Method. To describe the processes of scheduling classes applied the methodology of constructive-production modeling. From
the point of view of constructivism: on the basis of a number of structures with a given structure and content, it is necessary to complete
the construction of a schedule with a given structure and partly content. The development of the designer provides for the definition
of expandable carrier, signatures of relations and operations, as well as information support. The most difficult and essential
part is the creation of a set of substitution rules, which define the output process of the corresponding constructions.
Results. Developed a university course timetabling constructor and software that implements the proposed method.
Conclusions. The experiments confirmed the effectiveness of the proposed approach and the software that implements the proposed
method. This allows us to recommend it for use in practice in solving problems of scheduling classes.
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