Grouping genetic algorithms: an efficient method to solve the cell formation problem
Mathematics and Computers in Simulation - Special issue from the IMACS/IFAC international symposium on soft computing methods and applications: “SOFTCOM '99” (held in Athens, Greece)
Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
A Survey of Automated Timetabling
Artificial Intelligence Review
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
PATAT '97 Selected papers from the Second International Conference on Practice and Theory of Automated Timetabling II
Genetic algorithms and timetabling
Advances in evolutionary computing
CPGEA: a grouping genetic algorithm for material cutting plan generation
Computers and Industrial Engineering
Computers and Operations Research
A hybrid grouping genetic algorithm for the cell formation problem
Computers and Operations Research
Case-based selection of initialisation heuristics for metaheuristic examination timetabling
Expert Systems with Applications: An International Journal
A hybrid grouping genetic algorithm for the registration area planning problem
Computer Communications
Applying evolutionary computation to the school timetabling problem: The Greek case
Computers and Operations Research
Decision support for proposal grouping: A hybrid approach using knowledge rule and genetic algorithm
Expert Systems with Applications: An International Journal
A grouping genetic algorithm for the microcell sectorization problem
Engineering Applications of Artificial Intelligence
Near optimal citywide WiFi network deployment using a hybrid grouping genetic algorithm
Expert Systems with Applications: An International Journal
Computers and Operations Research
A novel grouping harmony search algorithm for the multiple-type access node location problem
Expert Systems with Applications: An International Journal
A new grouping genetic algorithm for clustering problems
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Solution approaches to the course timetabling problem
Artificial Intelligence Review
Hi-index | 12.06 |
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.