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ORCIDManuel Villalobos-Cid
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2020 – today
- 2024
[j6]Felipe-Andrés Bello Robles
, Manuel Villalobos-Cid, Max Chacón, Mario Inostroza-Ponta:
A multi-objective optimisation approach for the linear modelling of cerebral autoregulation system. Biosyst. 241: 105231 (2024)- [c17]Jorge Cubillos-Chaparro, Márcio Dorn, Manuel Villalobos-Cid, Mario Inostroza-Ponta:
A Multiobjective Evolutionary Algorithm for Colon Cancer Biomarkers Identification on Gene Expression Data. CIBCB 2024: 1-8 - 2023
- [j5]Manuel Villalobos-Cid, Márcio Dorn, Ángela Contreras, Mario Inostroza-Ponta:
An evolutionary algorithm based on parsimony for the multiobjective phylogenetic network inference problem. Appl. Soft Comput. 139: 110270 (2023) - [c16]Nicolás Mariángel, Juan Giglio, Sebastián Aliaga-Rojas, Manuel Villalobos-Cid, Mario Inostroza-Ponta:
Evaluating the incorporation of Biological Knowledge in multiobjective clustering of gene expression data. SCCC 2023: 1-8 - 2022
- [j4]Manuel Villalobos-Cid, César Rivera, Eduardo I. Kessi-Pérez, Mario Inostroza-Ponta:
A multi-modal algorithm based on an NSGA-II scheme for phylogenetic tree inference. Biosyst. 213: 104606 (2022) - [c15]Vicente Rivera-Rebolledo, Manuel Villalobos-Cid, Mario Inostroza-Ponta:
Improving solution diversity on NSGA-II for multi-objective clustering problems. SCCC 2022: 1-8 - 2021
- [c14]Sebastián Aliaga-Rojas, Manuel Villalobos-Cid, Márcio Dorn, Mario Inostroza-Ponta:
A multi-objective approach for the protein structure prediction problem. SCCC 2021: 1-8 - [c13]Juan Giglio, Gabriel Gaete-Lucero, Manuel Villalobos-Cid:
Classification of Chileans public hospitals based on healthcare production using clustering techniques. SCCC 2021: 1-8 - [c12]José Fernández Goycoolea, Mario Inostroza-Ponta, Manuel Villalobos-Cid, Mauricio Marín:
Single-solution based metaheuristic approach to a novel restricted clustering problem. SCCC 2021: 1-7 - 2020
- [j3]Manuel Villalobos-Cid, Francisco Salinas, Mario Inostroza-Ponta:
Total evidence or taxonomic congruence? A comparison of methods for combining biological evidence. J. Bioinform. Comput. Biol. 18(6): 2050040:1-2050040:17 (2020) - [c11]César Rivera, Mario Inostroza-Ponta, Manuel Villalobos-Cid:
A multimodal multi-objective optimisation approach to deal with the phylogenetic inference problem. CIBCB 2020: 1-7 - [c10]Angelo Carlier González, José Lillo, Mario Inostroza-Ponta, Manuel Villalobos-Cid:
Evaluating the categorisation of the public hospitals in Chile according to case-mix complexity: a genetic algorithm approach. SCCC 2020: 1-9 - [c9]Liliana Huallcca, Graciela Madrid Muñoz, José Mellado, Daniel Vega-Araya, Manuel Villalobos-Cid:
An informatics tool for class-to-class planning and academic-load evaluation. SCCC 2020: 1-5 - [c8]Nelson Troncoso, Luis Rojo-González, Óscar C. Vásquez, Rodrigo Acuña, Héctor Chávez, Manuel Villalobos-Cid:
Photovoltaic and Energy Storage Sizing Algorithm for the Chilean Distribution Tariff. SCCC 2020: 1-5
2010 – 2019
- 2019
- [j2]Manuel Villalobos-Cid, Márcio Dorn, Rodrigo Ligabue-Braun, Mario Inostroza-Ponta:
A Memetic Algorithm Based on an NSGA-II Scheme for Phylogenetic Tree Inference. IEEE Trans. Evol. Comput. 23(5): 776-787 (2019) - [c7]Juan Giglio, Mario Inostroza-Ponta, Manuel Villalobos-Cid:
A multi-objective optimisation evolutionary approach for the Multidimensional Scaling Problem. SCCC 2019: 1-8 - [c6]Manuel Villalobos-Cid, Maximiliano Orellana, Oscar C. Vásquez, Eduardo Pinto-Sothers, Mario Inostroza-Ponta:
Dealing with the Balanced Academic Curriculum Problem considering the Chilean Academic Credit Transfer System. SCCC 2019: 1-7 - 2018
- [c5]Manuel Villalobos-Cid, Márcio Dorn, Mario Inostroza-Ponta:
Performance Comparison of Multi-Objective Local Search Strategies to Infer Phylogenetic Trees. CEC 2018: 1-8 - [c4]Manuel Villalobos-Cid, Márcio Dorn, Mario Inostroza-Ponta:
Understanding the Relationship Between Decision and Objective Space in the Multi-Objective Phylogenetic Inference Problem. CEC 2018: 1-8 - 2017
- [c3]Benjamin Ruiz-Tagle, Manuel Villalobos-Cid, Márcio Dorn, Mario Inostroza-Ponta:
Evaluating the use of local search strategies for a memetic algorithm for the protein-ligand docking problem. SCCC 2017: 1-12 - [c2]Roberto Sandoval-Soto, Manuel Villalobos-Cid, Mario Inostroza-Ponta:
Tackling the bi-objective quadratic assignment problem by characterizing different memory strategies in a memetic algorithm. SCCC 2017: 1-12 - [c1]Manuel Villalobos-Cid, Daniel Vega-Araya, Mario Inostroza-Ponta:
Application of different multi-objective decision making techniques in the phylogenetic inference problem. SCCC 2017: 1-9 - 2016
- [j1]Manuel Villalobos-Cid, Max Chacón, Pedro Zitko, Mario Inostroza-Ponta:
A New Strategy to Evaluate Technical Efficiency in Hospitals Using Homogeneous Groups of Casemix - How to Evaluate When There is Not DRGs? J. Medical Syst. 40(4): 103:1-103:12 (2016)
Coauthor Index
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