Man

Felipe Andrés Cisternas Caneo

Líneas de Investigación


Metaheurísticas, Algoritmos Híbridos, Machine Learning, Algoritmos Bio-Inspirados, Optimización, Optimización Combinatorial, Metaheurísticas Caóticas

Educación

  •  Ingeniero Civil en Informática, PONTIFICIA UNIVERSIDAD CATOLICA DE VALPARAISO. Chile, 2020
  •  Magíster en Ingeniería Informática, PONTIFICIA UNIVERSIDAD CATOLICA DE VALPARAISO. Chile, 2021
  •  Licenciado en Ciencias de la Ingeniería, PONTIFICIA UNIVERSIDAD CATOLICA DE VALPARAISO. Chile, 2019
  •  Magíster en Ciencias de la Ingeniería Informática, PONTIFICIA UNIVERSIDAD CATOLICA DE VALPARAISO. Chile, 2024

Experiencia Académica

  •   Profesor Agregado Part Time

    PONTIFICIA UNIVERSIDAD CATOLICA DE VALPARAISO

    Facultad de Ingeniería

    Valparaíso, Chile

    2023 - A la fecha

  •   Profesor Hora Part Time

    UNIVERSIDAD TECNICA FEDERICO SANTA MARIA

    Quilpué, Chile

    2024 - A la fecha


 

Article (19)

Enhancing Reptile Search Algorithm Performance for the Knapsack Problem with Integration of Chaotic Map
How Is the Objective Function of the Feature Selection Problem Formulated?
A Binary Chaotic White Shark Optimizer
A Novel Approach to Combinatorial Problems: Binary Growth Optimizer Algorithm
Chaotic Binarization Schemes for Solving Combinatorial Optimization Problems Using Continuous Metaheuristics
Optimizing the Feature Selection Problem with Pendulum Search Algorithm: Binarization Strategies and Their Impacts
A Binary Black Widow Optimization Algorithm for Addressing the Cell Formation Problem Involving Alternative Routes and Machine Reliability
B-PSA: A Binary Pendulum Search Algorithm for the Feature Selection Problem
Binarization of Metaheuristics: Is the Transfer Function Really Important?
A New Learnheuristic: Binary SARSA - Sine Cosine Algorithm (BS-SCA)
Embedded Learning Approaches in the Whale Optimizer to Solve Coverage Combinatorial Problems
Population Size Management in a Cuckoo Search Algorithm Solving Combinatorial Problems
Swarm-Inspired Computing to Solve Binary Optimization Problems: A Backward Q-Learning Binarization Scheme Selector
A Comparison of Learnheuristics Using Different Reward Functions to Solve the Set Covering Problem
A Novel Learning-Based Binarization Scheme Selector for Swarm Algorithms Solving Combinatorial Problems
Embedding Q-Learning in the selection of metaheuristic operators: The enhanced binary grey wolf optimizer case
Q-learnheuristics: Towards data-driven balanced metaheuristics
Reinforcement Learning Based Whale Optimizer
Analysis and Prediction of Engineering Student Behavior and Their Relation to Academic Performance Using Data Analytics Techniques

Review (2)

Feature Selection Problem and Metaheuristics: A Systematic Literature Review about Its Formulation, Evaluation and Applications
Continuous Metaheuristics for Binary Optimization Problems: An Updated Systematic Literature Review
5
Ricardo Soto

Director

Escuela de Ingeniería Informática - PUCV

Valparaiso, Chile

2
Alvaro Peña

Profesor Titular - Consejero Académico

Escuela Ingeniería en Construcción

Pontificia Universidad Católica de Valparaíso

Valparaíso, Chile

1
CLAUDIO ELÓRTEGUI

Director

Pontificia Universidad Católica de Valparaíso

Valparaíso, Chile

5
José Barrera

Profesor

Marketing y Tecnologías

Pontificia Universidad Católica de Valparaíso

Valparaíso, Chile

13
Marcelo Becerra

Profesor Asociado

Escuela de Ingeniería Informática

Pontificia Universidad Católica de Valparaíso

Valparaíso, Chile