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The generalized balanced academic curriculum problem with heterogeneous classes

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Abstract

We propose an extension of the Generalized Balanced Academic Curriculum Problem (GBACP), a relevant planning problem arising in many universities. The problem consists of assigning courses to teaching terms and years, satisfying a set of precedence constraints and balancing students’ load among terms. Differently from the original GBACP formulation, in our case, the same course can be assigned to different years for different curricula (i.e., the predetermined sets of courses from which a student can choose), leading to a more complex solution space.

The problem is tackled by both Integer Programming (IP) methods and combinations of metaheuristics based on local search. The experimental analysis shows that the best results are obtained by means of a two-stage metaheuristic that first computes a solution for the underlying GBACP and then refines it by searching in the extended solution space.

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Notes

  1. In this sum implicit binary variables, such those for modeling the min/max operators, are not included.

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Acknowledgements

The authors thank Marco Chiarandini for many fruitful discussions about the GBAC and GBAC-HC problems.

The access to IBM Ilog CPLEX 12.2 has been possible through the IBM Academic Initiative.

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Correspondence to Luca Di Gaspero.

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Ceschia, S., Di Gaspero, L. & Schaerf, A. The generalized balanced academic curriculum problem with heterogeneous classes. Ann Oper Res 218, 147–163 (2014). https://doi.org/10.1007/s10479-013-1358-8

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