Dra. Adriana Menchaca Méndez

Email: amenchaca@enesmorelia.unam.mx

Profesora Asociada C de Tiempo Completo – (ENES Morelia)

Recibió el grado de Doctora en Ciencias en Computación en 2015 en el Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (Departamento de Computación).

Áreas de interés: Optimización mono-objetivo y multi-objetivo, computación evolutiva, aprendizaje máquina.

Artículos de revista:

  • Adriana Menchaca-Mendez and Carlos A. Coello Coello. An alternative hypervolume-based selection mechanism for multi-objective evolutionary algorithms, Soft Computing, August 2015.
  • Adriana Menchaca-Mendez and Carlos A. Coello Coello. Selection Mechanisms based on the Maximin Fitness Function to solve Multi-Objective Optimization Problems, Information Sciences, March 2016.

Artículos de Congreso Internacional:

  1. Adriana Menchaca-Mendez and Carlos A. Coello Coello. GDE-MOEA: A New MOEA based on the Generational Distance indicator and ε-dominance, In 2015 IEEE Congress on Evolutionary Computation (CEC’2015), Sendai, Japan, May 2015.
  2. Adriana Menchaca-Mendez and Carlos A. Coello Coello. GD-MOEA: A New Multi-Objective Evolutionary Algorithm based on the Generational Distance Indicator In Evolutionary Multi-Criterion Optimization, 7th International Conference, EMO 2015, Guimaraes, Portugal, March 2015.
  3. Adriana Menchaca-Mendez and Elizabeth Montero and María-Cristina Riff and Carlos A. Coello Coello. A More Efficient Selection Scheme in iSMS-EMOA, In 14th edition of the Ibero-American Conference on Artificial Intelligence (IBERAMIA’2014), Santiago, Chile, December 2014.
  4. Adriana Menchaca-Mendez and Carlos A. Coello Coello. MH-MOEA: A New Multi-Objective Evolutionary Algorithm based on the Maximin Fitness Function and the Hypervolume Indicator, In Parallel Problem Solving from Nature (PPSN XIII). 13th International Conference, Ljubljana, Slovenia, September 2014.
  5. Adriana Menchaca-Mendez and Carlos A. Coello Coello. MD-MOEA: A New MOEA based on the Maximin Fitness Function and Euclidean Distances between Solutions, In 2014 IEEE Congress on Evolutionary Computation (CEC’2014), Beijing, China, July 2014.
  6. Adriana Menchaca-Mendez and Carlos A. Coello Coello. A New Selection Mechanism Based on Hy- pervolume and its Locality Property. In 2013 IEEE Congress on Evolutionary Computation (CEC’2013), Cancún, México, June 2013.
  7. Adriana Menchaca-Mendez and Carlos A. Coello Coello. Selection Operators based on Maximin Fitness Function for Multi-Objective Evolutionary Algorithms. In Evolutionary Multi-Criterion Optimization, 7th International Conference, EMO 2013, Sheffield, UK, March 2013.
  1. Adriana Menchaca-Mendez and Carlos A. Coello Coello. Solving Multi-Objective Optimization Problems using Differential Evolution and a Maximin Selection Criterion. In 2012 IEEE Congress on Evolutionary Computation (CEC’2012), Brisbane, Australia, June 2012.
  2. Adriana Menchaca-Mendez and Carlos A. Coello Coello. A new proposal to hybridize the Nelder-Mead method to a differential evolution algorithm for constrained optimization. In 2009 IEEE Congress on Evolutionary Computation (CEC’2009), Trondheim, Norway, May 2009.