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Professor DARIO LANDA SILVA's Outputs (3)

Great deluge with non-linear decay rate for solving course timetabling problems (2008)
Presentation / Conference Contribution
Landa-Silva, D., & Obit, J. H. (2008, September). Great deluge with non-linear decay rate for solving course timetabling problems. Presented at 2008 4th International IEEE Conference Intelligent Systems, IS 2008, Varna, Bulgaria

Course timetabling is the process of allocating, subject to constraints, limited rooms and timeslots for a set of courses to take place. Usually, in addition to constructing a feasible timetable (all constraints satisfied), there are desirable goals... Read More about Great deluge with non-linear decay rate for solving course timetabling problems.

Evolutionary multi-objective simulated annealing with adaptive and competitive search direction (2008)
Presentation / Conference Contribution
Li, H., & Landa-Silva, D. (2008, June). Evolutionary multi-objective simulated annealing with adaptive and competitive search direction. Presented at 2008 IEEE Congress on Evolutionary Computation, CEC 2008, Hong Kong, China

In this paper, we propose a population-based implementation of simulated annealing to tackle multi-objective optimisation problems, in particular those of combinatorial nature. The proposed algorithm is called Evolutionary Multiobjective Simulated An... Read More about Evolutionary multi-objective simulated annealing with adaptive and competitive search direction.

Adaptive and assortative mating scheme for evolutionary multi-objective algorithms (2008)
Book Chapter
Le, K., & Landa-Silva, D. (2008). Adaptive and assortative mating scheme for evolutionary multi-objective algorithms. In Artificial Evolution: 8th International Conference, Evolution Artificielle, EA 2007, Tours, France, October 29-31, 2007, Revised Selected Papers (172-183). Springer Verlag. https://doi.org/10.1007/978-3-540-79305-2_15

We are interested in the role of restricted mating schemes in the context of evolutionary multi-objective algorithms. In this paper, we propose an adaptive assortative mating scheme that uses similarity in the decision space (genotypic assortative ma... Read More about Adaptive and assortative mating scheme for evolutionary multi-objective algorithms.