Browsing by Author "Rosa, Agostinho C."
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- A hybrid shuffled frog-leaping algorithm for the university examination timetabling problemPublication . Leite, Nuno; Melicio, Fernando; Rosa, Agostinho C.The problem of examination timetabling is studied in this work. We propose a hybrid solution heuristic based on the Shuffled Frog-Leaping Algorithm (SFLA) for minimising the conflicts in the students's exams. The hybrid algorithm, named Hybrid SFLA (HSFLA), improves a population of frogs (solutions) by iteratively optimising each memeplex, and then shuffling the memeplexes in order to distribute the best performing frogs by the memeplexes. In each iteration the frogs are improved based on three operators: crossover and mutation operators, and a local search operator based on the Simulated Annealing metaheuristic. For the mutation and local search, we use two well known neighbourhood structures. The performance of the proposed method is evaluated on the 13 instances of the Toronto datasets from the literature. Computational results show that the HSFLA is competitive with state-of-the-art methods, obtaining the best results on average in seven of the 13 instances.
- A shuffled complex evolution algorithm for the examination timetabling problemPublication . Leite, Nuno; Melicio, Fernando; Rosa, Agostinho C.In this work two instances of the examination timetabling problem are studied and solved using memetic algorithms. The first is the uncapacitated single-epoch problem instance. In the second problem instance two examination epochs are considered, with different durations. The memetic algorithm, named Shuffled Complex Evolution Algorithm, uses a population organized into sets called complexes which evolve independently using a recombination and local search operators. Population diversity is preserved by means of the recombination operator and a special solution update mechanism. Experimental evaluation was carried out on the public uncapacitated Toronto benchmarks (single epoch) and on the ISEL-DEETC department examination benchmark (two epochs). Results show that the algorithm is competitive on the Toronto benchmarks, attaining a new lower bound on one benchmark. In the ISEL-DEETC benchmark, the algorithm attains a lower cost when compared with the manual solution.