Authors:
Nuno Leite
1
;
Fernando Melício
2
and
Agostinho Rosa
3
Affiliations:
1
ISEL - Lisbon Polytechnic Institute, Portugal
;
2
ISEL - Lisbon Polytechnic Institute and LaSEEB - System and Robotics Institute, Portugal
;
3
LaSEEB - System and Robotics Institute, IST and TU-Lisbon, Portugal
Keyword(s):
Examination Timetabling Problem, Toronto Benchmarks, Memetic Algorithm, Shuffled Frog-Leaping Algorithm.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolution Strategies
;
Evolutionary Computing
;
Genetic Algorithms
;
Hybrid Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Memetic Algorithms
;
Soft Computing
;
Swarm/Collective Intelligence
Abstract:
Shuffled Frog-Leaping Algorithm (SFLA) is a recently proposed memetic meta-heuristic algorithm for solving
combinatorial optimisation problems. SFLA has both global and local search capabilities, and great convergence
speed towards the global optimum. Compared to a genetic algorithm, the experimental results show
an effective reduction of the number of evaluations required to find the global optimal solution. The Examination
Timetabling Problem (ETTP) is a complex combinatorial optimisation problem faced by schools and
universities every epoch. In this work, we apply the Shuffled Frog-Leaping Algorithm to solve the ETTP.
The evolution step of the algorithm, specifically the local exploration in the submemeplex is carefully adapted
based on the prototype SFLA. The algorithm was evaluated on the standard Toronto benchmark instances,
and the preliminary experimental results obtained are comparable to those produced by state of art algorithms
while requiring much less time.