Authors:
Nuno Leite
1
;
Fernando Melício
2
and
Agostinho C. Rosa
3
Affiliations:
1
Instituto Superior de Engenharia de Lisboa/ADEETC, Instituto Superior Técnico and Universidade de Lisboa, Portugal
;
2
Institute for Systems and Robotics/LaSEEB and, Portugal
;
3
Instituto Superior Técnico, Universidade de Lisboa and Instituto de Sistemas e Robótica/LaSEEB, Portugal
Keyword(s):
Examination Timetabling, Shuffled Complex Evolution Algorithm, Memetic Computing, Great Deluge Algorithm, Toronto Benchmarks, Two-Epoch Examination Timetabling.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Genetic Algorithms
;
Hybrid Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Memetic Algorithms
;
Society and Cultural Aspects of Evolution
;
Soft Computing
;
Swarm/Collective Intelligence
Abstract:
In this work we present a memetic algorithm for solving examination timetabling problems. Two problems are analysed and solved. The first one is the well-studied single-epoch problem. The second problem studied
is an extension of the standard problem where two examination epochs are considered, with different durations. The proposed memetic algorithm inherits the population structure of the Shuffled Complex Evolution
algorithm, where the population is organized into sets called complexes. These complexes are evolved independently and then shuffled in order to generate the next generation complexes. In order to explore new
solutions, a crossover between two complex’s solutions is done. Then, a random solution selected from the top best solutions is improved, by applying a local search step where the Great Deluge algorithm is employed. Experimental evaluation was carried out on the public uncapacitated Toronto benchmarks (single epoch) and on the ISEL-DEETC department examination bench
mark (two epochs). Experimental results show that the
proposed algorithm is efficient and competitive on the Toronto benchmarks with other algorithms from the literature. Relating the ISEL-DEETC benchmark, the algorithm attains a lower cost when compared with the
manual solution.
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