Auraham Camacho

auraham.camacho at

I received the Ph.D. degree from the Center for Research and Advanced Studies (Cinvestav Unidad Tamaulipas), advised by Dr. Gregorio Toscano and Dr. Ricardo Landa. I am interested in evolutionary algorithms, multi- and many-objective optimization.


Software Developer Oracle Mexico Development Center (2021-present).

Ph.D. Cinvestav Unidad Tamaulipas. Thesis: On the Use of Scalarizing Functions to Solve Many-Objective Optimization Problems. Advisors: Dr. Gregorio Toscano and Dr. Ricardo Landa (2015-2020).

Resarch stay Southern University of Science and Technology. Advisor: Dr. Hisao Ishibuchi (2018-2019).

M.Sc. Cinvestav Unidad Tamaulipas. Thesis: Study of hybrid schemes for the simultaneous use of different formulations of a multi-objective optimization problem. Advisor: Dr. Gregorio Toscano (2012-2014).

B.S. Instituto Tecnológico de Matamoros (2007-2011).


Another Difficulty of Inverted Triangular Pareto Fronts for Decomposition-Based Multi-Objective Algorithms. Linjun He, Auraham Camacho, Hisao Ishibuchi. GECCO 2020 (Best Paper Award). [paper]

A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization. Kanzhen Wan, Cheng He, Auraham Camacho, Ke Shang, Rang Cheng, and Hisao Ishibuchi. CEC 2019. [paper]

Indicator-based Weight Adaptation for Solving Many-Objective Optimization Problems. Auraham Camacho, Gregorio Toscano, Ricardo Landa, and Hisao Ishibuchi. EMO 2019. [paper] [code]


Decomposition. This project contains a Python implementation of a search algorithm called Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D). This algorithm decomposes a problem into subproblems that are then solved collaboratively. It uses Numpy and Scipy for number crushing. [paper] [code]

Very Fast Nondominated Sorting. This project contains a concurrent implementation of the Very Fast Non-dominated Sorting (VFNS) in Python. This algorithm allows us to arrange a set of points into groups according to the quality of each point. We then compare each pair of points. Since each comparison is independent, we can do it concurrently with VFNS. [paper] [code]

Diversity Comparison Indicator. This project contains a Python implementation of the Diversity Comparison Indicator (DCI). This indicator is often used for assessing the performance of an evolutionary algorithm in terms of diversity. [paper] [code]


Latex template for presentations. This is the latex source code that I commonly use for my presentations. Feel free to use it. [code]