The generalized balanced academic curriculum problem with heterogeneous classes

Sara Ceschia (), Luca Di Gaspero () and Andrea Schaerf ()

Annals of Operations Research, 2014, vol. 218, issue 1, 147-163

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. Copyright Springer Science+Business Media New York 2014

Keywords: Timetabling; Simulated Annealing; Academic Planning; Mixed integer quadratic programming (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10479-013-1358-8

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