Application of different multi-objective decision making techniques in the phylogenetic inference problem

Villalobos-Cid, M., Vega-Araya, D., & Inostroza-Ponta, M. (2017). Application of different multi-objective decision making techniques in the phylogenetic inference problem. In 2017 36th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–9). 2017 36th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc.2017.8405145.

Evaluating the use of local search strategies for a memetic algorithm for the protein-ligand docking problem

Ruiz-Tagle, B., Villalobos-Cid, M., Dorn, M., & Inostroza-Ponta, M. (2017). Evaluating the use of local search strategies for a memetic algorithm for the protein-ligand docking problem. In 2017 36th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–12). 2017 36th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc.2017.8405141.

Tackling the bi-objective quadratic assignment problem by characterizing different memory strategies in a memetic algorithm

Sandoval-Soto, R., Villalobos-Cid, M., & Inostroza-Ponta, M. (2017). Tackling the bi-objective quadratic assignment problem by characterizing different memory strategies in a memetic algorithm. In 2017 36th International Conference of the Chilean Computer Science Society (SCCC) (pp. 1–12). 2017 36th International Conference of the Chilean Computer Science Society (SCCC). IEEE. https://doi.org/10.1109/sccc.2017.8405140.

Using local search strategies to improve the performance of NSGA-II for the Multi-Criteria Minimum Spanning Tree problem

Párraga-Álava, J., Dorn, M., & Inostroza-Ponta, M. (2017). Using local search strategies to improve the performance of NSGA-II for the Multi-Criteria Minimum Spanning Tree problem. En 2017 IEEE Congress on Evolutionary Computation (CEC 2017) (pp. 1119–1126). IEEE. https://doi.org/10.1109/CEC.2017.7969432

An evolutionary multi-agent algorithm to explore the high degree of selectivity in three-dimensional protein structures

De Lima Corrêa, L., Inostroza-Ponta, M., & Dorn, M. (2017). An evolutionary multi-agent algorithm to explore the high degree of selectivity in three-dimensional protein structures. En 2017 IEEE Congress on Evolutionary Computation (CEC 2017) (pp. 1111–1118). IEEE. https://doi.org/10.1109/CEC.2017.7969431

A bi-objective model for gene clustering combining expression data and external biological knowledge

Párraga-Álava, J., & Inostroza-Ponta, M. (2017). A bi-objective model for gene clustering combining expression data and external biological knowledge. En Proceedings of the 42nd Latin American Computing Conference, CLEI 2016. IEEE. https://doi.org/10.1109/CLEI.2016.7833327