1. A mathematical programming tool for an efficient decision-making on teaching assignment under non-regular time schedules
- Author
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D. Pérez-Perales, P. Solano Cutillas, and M. M. E. Alemany Díaz
- Subjects
0209 industrial biotechnology ,Schedule ,Operations research ,Process (engineering) ,Computer science ,Strategy and Management ,media_common.quotation_subject ,0211 other engineering and technologies ,Computational intelligence ,02 engineering and technology ,Non-regular schedules ,Management Science and Operations Research ,Model validation ,020901 industrial engineering & automation ,Mixed integer linear programming ,Management of Technology and Innovation ,Quality (business) ,media_common ,Numerical Analysis ,021103 operations research ,Academic year ,Subject (documents) ,Teaching assignment problem ,08.- Fomentar el crecimiento económico sostenido, inclusivo y sostenible, el empleo pleno y productivo, y el trabajo decente para todos ,Computational Theory and Mathematics ,Order (business) ,Modeling and Simulation ,ORGANIZACION DE EMPRESAS ,Type of credits ,Statistics, Probability and Uncertainty ,Time compatibility - Abstract
[EN] In this paper, an optimization tool based on a MILP model to support the teaching assignment process is proposed. It considers not only hierarchical issues among lecturers but also their preferences to teach a particular subject, the non-regular time schedules throughout the academic year, different type of credits, number of groups and other specific characteristics. Besides, it adds restrictions based on the time compatibility among the different subjects, the lecturers' availability, the maximum number of subjects per lecturer, the maximum number of lecturers per subject as well as the maximum and minimum saturation level for each lecturer, all of them in order to increase the teaching quality. Schedules heterogeneity and other features regarding the operation of some universities justify the usefulness of this model since no study that deals with all of them has been found in the literature review. Model validation has been performed with two real data sets collected from one academic year schedule at the Spanish University Universitat Politecnica de Valencia.
- Published
- 2022
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