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Pipelining Memetic Algorithms, Constraint Satisfaction, and Local Search for Course Timetabling.
- Source :
- Micai 2009: Advances in Artificial Intelligence; 2009, p408-419, 12p
- Publication Year :
- 2009
-
Abstract
- This paper introduces a hybrid algorithm that combines local search and constraint satisfaction techniques with memetic algorithms for solving Course Timetabling hard problems. These problems require assigning a set of courses to a predetermined finite number of classrooms and periods of time, complying with a complete set of hard constraints while maximizing the consistency with a set of preferences (soft constraints). The algorithm works in a three-stage sequence: first, it creates an initial population of approximations to the solution by partitioning the variables that represent the courses and solving each partition as a constraint-satisfaction problem; second, it reduces the number of remaining hard and soft constraint violations applying a memetic algorithm; and finally, it obtains a complete and fully consistent solution by locally searching around the best memetic solution. The approach produces competitive results, always getting feasible solutions with a reduced number of soft constraints inconsistencies, when compared against the methods running independently. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISBNs :
- 9783642052576
- Database :
- Complementary Index
- Journal :
- Micai 2009: Advances in Artificial Intelligence
- Publication Type :
- Book
- Accession number :
- 76845089
- Full Text :
- https://doi.org/10.1007/978-3-642-05258-3_36