Title | ||
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A hybrid grouping genetic algorithm for assigning students to preferred laboratory groups |
Abstract | ||
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This paper presents a novel application of the hybrid grouping genetic algorithm in a problem related to university timetabling. Specifically, the assignment of students to laboratory groups is tackled. This problem includes an important constraint of capacity, due to laboratories usually have a maximum number of equips or computers available, so the number of total students in a group is constrained to be equal or less than the capacity of the laboratory. In addition, our approach considers the case in which the students provide a sorted list of preferred laboratory groups, so the objective of the assignment must take this point into account. A variation of the problem in which a balanced number of students per group is required (lecturer preferences) is also studied in this paper. The performance of the approach is shown in different test problems and in a real application in a Spanish University. |
Year | DOI | Venue |
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2009 | 10.1016/j.eswa.2008.09.020 | Expert Syst. Appl. |
Keywords | Field | DocType |
real application,different test problem,timetabling,hybrid grouping genetic algorithm,laboratory group,balanced number,grouping genetic algorithms,combinatorial optimization,assignment problems,novel application,important constraint,maximum number,assigning student,preferred laboratory group,spanish university,assignment problem | Weapon target assignment problem,Mathematical optimization,Computer science,Generalized assignment problem,Combinatorial optimization,Artificial intelligence,Machine learning,Genetic algorithm | Journal |
Volume | Issue | ISSN |
36 | 3 | Expert Systems With Applications |
Citations | PageRank | References |
17 | 0.75 | 16 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Luis E. Agustín-Blas | 1 | 28 | 2.12 |
Sancho Salcedo-Sanz | 2 | 580 | 71.21 |
Emilio G. Ortiz-García | 3 | 140 | 10.54 |
Antonio Portilla-Figueras | 4 | 147 | 19.07 |
Ángel M. Pérez-Bellido | 5 | 130 | 11.71 |