| KEYWORD |
Resource allocation techniques for planning the teaching timetable
keywords COMBINATORIAL OPTIMIZATION, COMPUTATIONAL COMPLEXITY THEORY, RESOURCES ALLOCATION, TEACHING
Reference persons RENATO FERRERO
Research Groups DAUIN - GR-05 - ELECTRONIC CAD & RELIABILITY GROUP - CAD
Thesis type RESEARCH AND DEVELOPMENT
Description The topic of the thesis concerns the planning of the timetable of the bachelor and master's degree courses provided by the ICM (Computer Engineering, Cinema and Mechatronics) and ETF (Electronics, Telecommunications and Physics) colleges of Politecnico di Torino. The timetable is subject to numerous constraints, such as the compatibility between compulsory courses for a given orientation, the involvement of teachers in multiple courses, the availability of classrooms and laboratories, a correct daily balance (avoiding numerous consecutive lessons or long empty periods between lessons), etc. Correct modeling allows us to distinguish the constraints between hard constraints and soft constraints. The timetable is then obtained by solving an optimization problem, in which it is necessary to satisfy all the hard constraints and maximize an objective function that considers the soft constraints.
A first implementation of the solution was created in Python, which includes: the import of input information (teaching, study plans, teachers, classrooms), the coding of constraints in the form of mathematical equations, the optimization process, the validation of results. The thesis activity concerns the improvement of the solution and the development of new features, such as: the insertion of further constraints to complete the modeling of the problem, a correct balancing of penalties for the currently implemented constraints, the development of a graphical interface to facilitate program input/output.
Required skills Python programming, operations research
Deadline 27/10/2024
PROPONI LA TUA CANDIDATURA