Constraint-based model design for timetabling problems in secondary schools

Nogareda, Ana Maria; Camacho, David

doi:10.1109/inista.2015.7276777

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…Ninety schools are impacted by this new program, which corresponds to three grades (around years 12 to 15). This new program is briefly described in this section, for more details about it, see [17].…”

Section: Description Of the Classes' Setting Up Problemmentioning

confidence: 99%

“…This problem occurs in secondary schools in Canton de Vaud (Vaud), a French part of Switzerland. A new educational system was launched in 2013, [16,17]. Before 2013, students were allocated to classes and then a traditional timetabling problem was solved with commercial software in almost all schools in Vaud, since all students in a class attended the same lessons.…”

Section: Introductionmentioning

confidence: 99%

“…Regarding similarity, classes have to distribute students in a fair way among them in order to satisfy this objective as much as possible. In [17], a complete model that combined the allocation and the timetabling problems was proposed, but not solved.…”

Section: Introductionmentioning

confidence: 99%

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A Constraint-Based Approach for Classes Setting-Up Problems in Secondary Schools

Nogareda¹,

Camacho²

2017

Int. j. simul. model.

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In this paper, we present the problem of allocating students to classes in Swiss secondary schools, where students have different profiles due to their level in some fields or to the options they attend. The pedagogical objective is to have a high diversity of profiles within a class and similarity between classes. In order to achieve this goal, the problem is modelled as a resource allocation problem (RAP), where students are resources, using a constraint satisfaction optimisation approach (CSOP). The RAP is then solved in two different ways, with a solver for CSOP, and with an ant colony optimisation algorithm (ACO). Eight real datasets are used to compare their performance. The ACO algorithm provides better solutions than the CSOP solver in a shorter time. Results show that the pheromones used in the ACO help to find better solutions in a much smaller amount of time. The short computation time enables the school's directors to simulate different compositions of their future classes before having the final results of the last exams.

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Section: Description Of the Classes' Setting Up Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%