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ORCIDIván Amaya
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- affiliation: Tecnologico de Monterrey, School of Engineering and Sciences, Mexico
- affiliation: Industrial University of Santander, School of Electrical, Electronic and Telecommunications Engineerings, Colombia
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Journal Articles
- 2024
[j22]Maria Torcoroma Benavides-Robles
, Gerardo Humberto Valencia-Rivera, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss:
Robotic Mobile Fulfillment System: A Systematic Review. IEEE Access 12: 16767-16782 (2024)- [j21]Gerardo Humberto Valencia-Rivera, Maria Torcoroma Benavides-Robles, Alonso Vela Morales, Iván Amaya, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Juan Gabriel Aviña-Cervantes:
A systematic review of metaheuristic algorithms in electric power systems optimization. Appl. Soft Comput. 150: 111047 (2024) - [j20]Jose M. Tapia-Avitia, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Nelishia Pillay:
Analysing hyper-heuristics based on Neural Networks for the automatic design of population-based metaheuristics in continuous optimisation problems. Swarm Evol. Comput. 89: 101616 (2024) - 2023
- [j19]Daniel F. Zambrano-Gutierrez, Jorge Mario Cruz-Duarte, Juan Gabriel Aviña-Cervantes, José Carlos Ortiz-Bayliss, Jesus J. Yanez-Borjas, Iván Amaya:
Automatic Design of Metaheuristics for Practical Engineering Applications. IEEE Access 11: 7262-7276 (2023) - 2022
- [j18]Alonso Vela, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya:
Beyond Hyper-Heuristics: A Squared Hyper-Heuristic Model for Solving Job Shop Scheduling Problems. IEEE Access 10: 43981-44007 (2022) - [j17]Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya:
MatHH: A Matlab-based Hyper-Heuristic framework. SoftwareX 18: 101047 (2022) - 2021
- [j16]Alonso Vela, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya:
Tailoring Job Shop Scheduling Problem Instances Through Unified Particle Swarm Optimization. IEEE Access 9: 66891-66914 (2021) - [j15]Melissa Sánchez, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya:
Sequence-Based Selection Hyper-Heuristic Model via MAP-Elites. IEEE Access 9: 116500-116527 (2021) - [j14]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Rodrigo Correa:
Solving microelectronic thermal management problems using a generalized spiral optimization algorithm. Appl. Intell. 51(8): 5622-5643 (2021) - [j13]Frumen Olivas, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín:
Enhancing Hyperheuristics for the Knapsack Problem through Fuzzy Logic. Comput. Intell. Neurosci. 2021: 8834324:1-8834324:17 (2021) - [j12]Cristian Jimenez, Iván Amaya, Rodrigo Correa:
SCSV_IPS: A software for the estimation of the shear coefficient of spin viscosity during the movement of a ferrofluid under the effect of an external rotating magnetic field. SoftwareX 14: 100668 (2021) - [j11]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín, Yong Shi:
Hyper-Heuristics to customise metaheuristics for continuous optimisation. Swarm Evol. Comput. 66: 100935 (2021) - 2020
- [j10]Melissa Sánchez, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Hector G. Ceballos, Hugo Terashima-Marín, Iván Amaya:
A Systematic Review of Hyper-Heuristics on Combinatorial Optimization Problems. IEEE Access 8: 128068-128095 (2020) - [j9]Cristian Jimenez, Iván Amaya, Rodrigo Correa:
SpinUpFlowDescriptor: A MATLAB toolbox for ferrofluids materials under moderate and high amplitude and frequency of magnetic rotating fields in a spin-up geometry. SoftwareX 12: 100567 (2020) - [j8]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Yong Shi:
CUSTOMHyS: Customising Optimisation Metaheuristics via Hyper-heuristic Search. SoftwareX 12: 100628 (2020) - 2019
- [j7]Luis Fernando Plata-González, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín, Carlos A. Coello Coello:
Evolutionary-based tailoring of synthetic instances for the Knapsack problem. Soft Comput. 23(23): 12711-12728 (2019) - 2018
- [j6]Iván Amaya, José Carlos Ortiz-Bayliss, Alejandro Rosales-Pérez, Andrés Eduardo Gutiérrez-Rodríguez, Santiago E. Conant-Pablos, Hugo Terashima-Marín, Carlos A. Coello Coello:
Enhancing Selection Hyper-Heuristics via Feature Transformations. IEEE Comput. Intell. Mag. 13(2): 30-41 (2018) - [j5]José Carlos Ortiz-Bayliss, Iván Amaya, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín:
Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems. Comput. Intell. Neurosci. 2018: 6103726:1-6103726:14 (2018) - 2015
- [j4]Iván Amaya, Jorge Cruz, Rodrigo Correa:
Harmony Search algorithm: a variant with Self-regulated Fretwidth. Appl. Math. Comput. 266: 1127-1152 (2015) - [j3]Iván Amaya, Rodrigo Correa:
Finding resonant frequencies of microwave cavities through a modified harmony search algorithm. Int. J. Bio Inspired Comput. 7(5): 285-295 (2015) - 2014
- [j2]Jhonatan Contreras, Iván Amaya, Rodrigo Correa:
An improved variant of the conventional Harmony Search algorithm. Appl. Math. Comput. 227: 821-830 (2014) - 2013
- [j1]Oscar Pérez, Iván Amaya, Rodrigo Correa:
Numerical solution of certain exponential and non-linear Diophantine systems of equations by using a discrete particle swarm optimization algorithm. Appl. Math. Comput. 225: 737-746 (2013)
Conference and Workshop Papers
- 2024
- [c28]Guillermo Pérez-Espinosa, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Nelishia Pillay:
Tailoring Metaheuristics for Designing Thermodynamic-Optimal Cooling Devices for Microelectronic Thermal Management Applications. CEC 2024: 1-8 - [c27]Daniel F. Zambrano-Gutierrez, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya, Juan Gabriel Aviña-Cervantes:
Beyond Traditional Tuning: Unveiling Metaheuristic Operator Trends in PID Control Tuning for Automatic Voltage Regulation. CEC 2024: 1-8 - 2023
- [c26]Gerardo Humberto Valencia-Rivera, José Carlos Ortiz-Bayliss, Jorge M. Cruz-Duarte, Iván Amaya, Juan Gabriel Aviña-Cervantes:
Hyper-Heuristics Meet Controller Design: Improving Electrical Grid Performance through Microgrids. CEC 2023: 1-8 - [c25]Alonso Vela, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya:
Recursive Hyper-Heuristics for the Job Shop Scheduling Problem. CEC 2023: 1-8 - [c24]Maria Torcoroma Benavides-Robles, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss, Iván Amaya:
On the Feasibility of Using a High-Level Solver within Robotic Mobile Fulfillment Systems. SSCI 2023: 1274-1279 - [c23]Daniel F. Zambrano-Gutierrez, Alberto C. Molina-Porras, Emmanuel Ovalle-Magallanes, Iván Amaya, José Carlos Ortiz-Bayliss, Juan Gabriel Aviña-Cervantes, Jorge M. Cruz-Duarte:
SIGNRL: A Population-Based Reinforcement Learning Method for Continuous Control. SSCI 2023: 1443-1448 - 2022
- [c22]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Nelishia Pillay:
A Transfer Learning Hyper-heuristic Approach for Automatic Tailoring of Unfolded Population-based Metaheuristics. CEC 2022: 1-8 - [c21]Jose M. Tapia-Avitia, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Nelishia Pillay:
A Primary Study on Hyper-Heuristics Powered by Artificial Neural Networks for Customising Population-based Metaheuristics in Continuous Optimisation Problems. CEC 2022: 1-8 - 2021
- [c20]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Nelishia Pillay:
Automated Design of Unfolded Metaheuristics and the Effect of Population Size. CEC 2021: 1155-1162 - [c19]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Nelishia Pillay:
Naïve Hyper-heuristic Online Learning to Generate Unfolded Population-based Metaheuristics to Solve Continuous Optimization Problems. SSCI 2021: 1-8 - 2020
- [c18]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín:
A Primary Study on Hyper-Heuristics to Customise Metaheuristics for Continuous optimisation. CEC 2020: 1-8 - [c17]Fernando Garza-Santisteban, Iván Amaya, Jorge Cruz, José Carlos Ortiz-Bayliss, Ender Özcan, Hugo Terashima-Marín:
Exploring Problem State Transformations to Enhance Hyper-heuristics for the Job-Shop Scheduling Problem. CEC 2020: 1-8 - [c16]Frumen Olivas, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín:
A Fuzzy Hyper-Heuristic Approach for the 0-1 Knapsack Problem. CEC 2020: 1-8 - [c15]Xavier Sánchez, José Carlos Ortiz-Bayliss, Iván Amaya, Jorge M. Cruz-Duarte, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín:
A Preliminary Study on Feature-independent Hyper-heuristics for the 0/1 Knapsack Problem. CEC 2020: 1-8 - [c14]Arturo Silva-Gálvez, Erick Lara-Cárdenas, Iván Amaya, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss:
A Preliminary Study on Score-Based Hyper-heuristics for Solving the Bin Packing Problem. MCPR 2020: 318-327 - [c13]Erick Lara-Cárdenas, Xavier Sánchez-Díaz, Iván Amaya, Jorge M. Cruz-Duarte, José Carlos Ortiz-Bayliss:
A Genetic Programming Framework for Heuristic Generation for the Job-Shop Scheduling Problem. MICAI (1) 2020: 284-295 - [c12]Arturo Silva-Gálvez, Jorge Orozco-Sanchez, Erick Lara-Cárdenas, José Carlos Ortiz-Bayliss, Iván Amaya, Jorge M. Cruz-Duarte, Hugo Terashima-Marín:
Discovering Action Regions for Solving the Bin Packing Problem through Hyper-heuristics. SSCI 2020: 822-828 - [c11]Erick Lara-Cárdenas, Arturo Silva-Gálvez, José Carlos Ortiz-Bayliss, Iván Amaya, Jorge M. Cruz-Duarte, Hugo Terashima-Marín:
Exploring Reward-based Hyper-heuristics for the Job-shop Scheduling Problem. SSCI 2020: 3133-3140 - 2019
- [c10]Fernando Garza-Santisteban, Roberto Sánchez-Pámanes, Luis Antonio Puente Rodríguez, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín:
A Simulated Annealing Hyper-heuristic for Job Shop Scheduling Problems. CEC 2019: 57-64 - [c9]Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos, Hugo Terashima-Marín:
Hyper-heuristics Reversed: Learning to Combine Solvers by Evolving Instances. CEC 2019: 1790-1797 - [c8]Erick Lara-Cárdenas, Xavier Sánchez-Díaz, Iván Amaya, José Carlos Ortiz-Bayliss:
Improving Hyper-heuristic Performance for Job Shop Scheduling Problems Using Neural Networks. MICAI 2019: 150-161 - [c7]Fernando Garza-Santisteban, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín:
Influence of Instance Size on Selection Hyper-Heuristics for Job Shop Scheduling Problems. SSCI 2019: 1708-1715 - 2018
- [c6]Bronson Duhart, Fernando Camarena, José Carlos Ortiz-Bayliss, Iván Amaya, Hugo Terashima-Marín:
An Experimental Study on Ant Colony Optimization Hyper-Heuristics for Solving the Knapsack Problem. MCPR 2018: 62-71 - [c5]Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos, Hugo Terashima-Marín, Carlos A. Coello Coello:
Tailoring Instances of the 1D Bin Packing Problem for Assessing Strengths and Weaknesses of Its Solvers. PPSN (2) 2018: 373-384 - 2017
- [c4]Iván Amaya, José Carlos Ortiz-Bayliss, Andrés Eduardo Gutiérrez-Rodríguez, Hugo Terashima-Marín, Carlos A. Coello Coello:
Improving hyper-heuristic performance through feature transformation. CEC 2017: 2614-2621 - [c3]Andrés Eduardo Gutiérrez-Rodríguez, José Carlos Ortiz-Bayliss, Alejandro Rosales-Pérez, Ivan M. Amaya-Contreras, Santiago E. Conant-Pablos, Hugo Terashima-Marín, Carlos A. Coello Coello:
Applying automatic heuristic-filtering to improve hyper-heuristic performance. CEC 2017: 2638-2644 - [c2]Fernando Gómez-Herrera, Rodolfo A. Ramirez-Valenzuela, José Carlos Ortiz-Bayliss, Iván Amaya, Hugo Terashima-Marín:
A Quartile-Based Hyper-heuristic for Solving the 0/1 Knapsack Problem. MICAI (1) 2017: 118-128 - 2015
- [c1]Jorge M. Cruz-Duarte, Juan Gabriel Aviña-Cervantes, Ivan M. Amaya-Contreras, Carlos Rodrigo Correa-Cely:
Design of an Optimal Heat Sink for Microelectronic Devices Using Entropy Generation Minimization. MICAI (Special Sessions) 2015: 231-235
Informal and Other Publications
- 2018
- [i1]Iván Amaya, José Carlos Ortiz-Bayliss, Alejandro Rosales-Pérez, Andrés Eduardo Gutiérrez-Rodríguez, Santiago E. Conant-Pablos, Hugo Terashima-Marín, Carlos A. Coello Coello:
Enhancing Selection Hyper-heuristics via Feature Transformations. CoRR abs/1812.05070 (2018)
Coauthor Index
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