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Hugo Terashima-Marín
Hugo Terashima
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2020 – today
- 2024
- [j33]Alonso Javier Amado-Garfias
, Santiago Enrique Conant-Pablos
Improving Armed People Detection on Video Surveillance Through Heuristics and Machine Learning Models. IEEE Access 12: 111818-111831 (2024) - [j32]Farman Ali Pirzado
Navigating the Pitfalls: Analyzing the Behavior of LLMs as a Coding Assistant for Computer Science Students - A Systematic Review of the Literature. IEEE Access 12: 112605-112625 (2024) - [j31]Alonso Javier Amado-Garfias, Santiago Enrique Conant-Pablos, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín:
Automatic Selection of Machine Learning Models for Armed People Identification. IEEE Access 12: 175952-175968 (2024) - [j30]Gerardo Ibarra-Vázquez
Gender prediction based on University students' complex thinking competency: An analysis from machine learning approaches. Educ. Inf. Technol. 29(3): 2721-2739 (2024) - [j29]Jose M. Tapia-Avitia, Jorge M. Cruz-Duarte
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) - [c81]Gerardo Ibarra-Vázquez, Hugo Terashima-Marín, Carlos A. Coello Coello:
Exploring Generative AIs as Population Variation Operator in Multi-objective Optimization Problems. CEC 2024: 1-8 - [c80]Julio Juárez, Carlos A. Brizuela, Hugo Terashima-Marín, Carlos A. Coello Coello:
Recombination Operators for the Multi-Objective Team Formation Problem in Social Networks. CEC 2024: 1-8 - [c79]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 - [c78]José Carlos Ortiz-Bayliss
Missing Data and Their Effect on Algorithm Selection for the Bin Packing Problem. MCPR 2024: 34-43 - 2023
- [j28]Mohd Anas Wajid
Neutrosophic-CNN-based image and text fusion for multimodal classification. J. Intell. Fuzzy Syst. 45(1): 1039-1055 (2023) - 2022
- [j27]Kevin B. Kwan-Loo, José Carlos Ortiz-Bayliss
Detection of Violent Behavior Using Neural Networks and Pose Estimation. IEEE Access 10: 86339-86352 (2022) - [j26]P. K. Gupta
COVID-WideNet - A capsule network for COVID-19 detection. Appl. Soft Comput. 122: 108780 (2022) - [j25]Mohammad Saif Wajid, Hugo Terashima-Marín
Violence Detection Approach based on Cloud Data and Neutrosophic Cognitive Maps. J. Cloud Comput. 11: 85 (2022) - [j24]Mohammad Saif Wajid, Hugo Terashima-Marín
Correction: Violence detection approach based on cloud data and Neutrosophic cognitive maps. J. Cloud Comput. 11: 100 (2022) - [c77]Jose M. Tapia-Avitia
A Primary Study on Hyper-Heuristics Powered by Artificial Neural Networks for Customising Population-based Metaheuristics in Continuous Optimisation Problems. CEC 2022: 1-8 - [i6]Roberto García-Torres, Alitzel Adriana Macias-Infante, Santiago Enrique Conant-Pablos
Combining Constructive and Perturbative Deep Learning Algorithms for the Capacitated Vehicle Routing Problem. CoRR abs/2211.13922 (2022) - 2021
- [j23]Frumen Olivas
Enhancing Hyperheuristics for the Knapsack Problem through Fuzzy Logic. Comput. Intell. Neurosci. 2021: 8834324:1-8834324:17 (2021) - [j22]Guillermo A. Martínez-Mascorro
Criminal Intention Detection at Early Stages of Shoplifting Cases by Using 3D Convolutional Neural Networks. Comput. 9(2): 24 (2021) - [j21]Carlos Tejeda-Ocampo
Improving Deep Interactive Evolution with a Style-Based Generator for Artistic Expression and Creative Exploration. Entropy 23(1): 11 (2021) - [j20]Felipe de la Rosa-Rivera, José I. Nuñez-Varela
Algorithm selection for solving educational timetabling problems. Expert Syst. Appl. 174: 114694 (2021) - [j19]Jorge M. Cruz-Duarte
Hyper-Heuristics to customise metaheuristics for continuous optimisation. Swarm Evol. Comput. 66: 100935 (2021) - [c76]Jesús Andrés Portillo-Quintero
A Straightforward Framework for Video Retrieval Using CLIP. MCPR 2021: 3-12 - [i5]Jesús Andrés Portillo-Quintero, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín:
A Straightforward Framework For Video Retrieval Using CLIP. CoRR abs/2102.12443 (2021) - 2020
- [j18]Melissa Sánchez
A Systematic Review of Hyper-Heuristics on Combinatorial Optimization Problems. IEEE Access 8: 128068-128095 (2020) - [j17]Jorge M. Cruz-Duarte
CUSTOMHyS: Customising Optimisation Metaheuristics via Hyper-heuristic Search. SoftwareX 12: 100628 (2020) - [c75]Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos
A Primary Study on Hyper-Heuristics to Customise Metaheuristics for Continuous optimisation. CEC 2020: 1-8 - [c74]Fernando Garza-Santisteban, Iván Amaya, Jorge Cruz, José Carlos Ortiz-Bayliss, Ender Özcan
Exploring Problem State Transformations to Enhance Hyper-heuristics for the Job-Shop Scheduling Problem. CEC 2020: 1-8 - [c73]Frumen Olivas, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos
A Fuzzy Hyper-Heuristic Approach for the 0-1 Knapsack Problem. CEC 2020: 1-8 - [c72]Xavier Sánchez
A Preliminary Study on Feature-independent Hyper-heuristics for the 0/1 Knapsack Problem. CEC 2020: 1-8 - [c71]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 - [c70]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 - [i4]Guillermo A. Martínez-Mascorro, José R. Abreu-Pederzini, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín:
Suspicious Behavior Detection on Shoplifting Cases for Crime Prevention by Using 3D Convolutional Neural Networks. CoRR abs/2005.02142 (2020) - [i3]Guillermo A. Martínez-Mascorro, José Carlos Ortiz-Bayliss, Hugo Terashima-Marín:
Detecting Suspicious Behavior: How to Deal with Visual Similarity through Neural Networks. CoRR abs/2007.15235 (2020) - [i2]Nihar Bendre, Hugo Terashima-Marín, Peyman Najafirad:
Learning from Few Samples: A Survey. CoRR abs/2007.15484 (2020)
2010 – 2019
- 2019
- [j16]Andrés Eduardo Gutiérrez-Rodríguez, Santiago E. Conant-Pablos
Selecting meta-heuristics for solving vehicle routing problems with time windows via meta-learning. Expert Syst. Appl. 118: 470-481 (2019) - [j15]Luis Fernando Plata-González, Iván Amaya, José Carlos Ortiz-Bayliss
Evolutionary-based tailoring of synthetic instances for the Knapsack problem. Soft Comput. 23(23): 12711-12728 (2019) - [c69]Fernando Garza-Santisteban, Roberto Sánchez-Pámanes, Luis Antonio Puente Rodríguez, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos
A Simulated Annealing Hyper-heuristic for Job Shop Scheduling Problems. CEC 2019: 57-64 - [c68]Iván Amaya, José Carlos Ortiz-Bayliss, Santiago E. Conant-Pablos
Hyper-heuristics Reversed: Learning to Combine Solvers by Evolving Instances. CEC 2019: 1790-1797 - [c67]Fernando Garza-Santisteban, Jorge M. Cruz-Duarte, Iván Amaya, José Carlos Ortiz-Bayliss, Santiago Enrique Conant-Pablos
Influence of Instance Size on Selection Hyper-Heuristics for Job Shop Scheduling Problems. SSCI 2019: 1708-1715 - 2018
- [j14]Alejandro Rosales-Pérez
MC2ESVM: Multiclass Classification Based on Cooperative Evolution of Support Vector Machines. IEEE Comput. Intell. Mag. 13(2): 18-29 (2018) - [j13]Iván Amaya, José Carlos Ortiz-Bayliss, Alejandro Rosales-Pérez
Enhancing Selection Hyper-Heuristics via Feature Transformations. IEEE Comput. Intell. Mag. 13(2): 30-41 (2018) - [j12]José Carlos Ortiz-Bayliss
Exploring the Impact of Early Decisions in Variable Ordering for Constraint Satisfaction Problems. Comput. Intell. Neurosci. 2018: 6103726:1-6103726:14 (2018) - [j11]Juan-Carlos Gomez
Evolutionary hyper-heuristics for tackling bi-objective 2D bin packing problems. Genet. Program. Evolvable Mach. 19(1-2): 151-181 (2018) - [j10]Jorge Rodríguez-Ruiz
Cluster validation using an ensemble of supervised classifiers. Knowl. Based Syst. 145: 134-144 (2018) - [c66]Alejandro Rosales-Pérez
Cooperative multi-objective evolutionary support vector machines for multiclass problems. GECCO 2018: 513-520 - [c65]Bronson Duhart, Fernando Camarena
An Experimental Study on Ant Colony Optimization Hyper-Heuristics for Solving the Knapsack Problem. MCPR 2018: 62-71 - [c64]Iván Amaya, José Carlos Ortiz-Bayliss
Tailoring Instances of the 1D Bin Packing Problem for Assessing Strengths and Weaknesses of Its Solvers. PPSN (2) 2018: 373-384 - [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) - 2017
- [c63]Iván Amaya, José Carlos Ortiz-Bayliss, Andrés Eduardo Gutiérrez-Rodríguez, Hugo Terashima-Marín
Improving hyper-heuristic performance through feature transformation. CEC 2017: 2614-2621 - [c62]Alejandro Rosales-Pérez
Evolutionary multilabel hyper-heuristic design. CEC 2017: 2622-2629 - [c61]Andrés Eduardo Gutiérrez-Rodríguez, José Carlos Ortiz-Bayliss, Alejandro Rosales-Pérez
Applying automatic heuristic-filtering to improve hyper-heuristic performance. CEC 2017: 2638-2644 - [c60]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 - 2016
- [j9]José Carlos Ortiz-Bayliss
Combine and conquer: an evolutionary hyper-heuristic approach for solving constraint satisfaction problems. Artif. Intell. Rev. 46(3): 327-349 (2016) - [j8]Jorge Humberto Moreno-Scott, José Carlos Ortiz-Bayliss
Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems. Comput. Intell. Neurosci. 2016: 7349070:1-7349070:15 (2016) - [j7]José Carlos Ortiz-Bayliss
A Neuro-evolutionary Hyper-heuristic Approach for Constraint Satisfaction Problems. Cogn. Comput. 8(3): 429-441 (2016) - [j6]Alejandro Sosa-Ascencio, Gabriela Ochoa
Grammar-based generation of variable-selection heuristics for constraint satisfaction problems. Genet. Program. Evolvable Mach. 17(2): 119-144 (2016) - [c59]Alejandro Sosa-Ascencio, Hugo Terashima-Marín
Grammar-based Selection Hyper-heuristics for Solving Irregular Bin Packing Problems. GECCO (Companion) 2016: 111-112 - [c58]David Espinoza-Nevárez, José Carlos Ortiz-Bayliss
Selection and Generation Hyper-heuristics for Solving the Vehicle Routing Problem with Time Windows. GECCO (Companion) 2016: 139-140 - 2015
- [c57]José Carlos Ortiz-Bayliss
A Recursive Split, Solve, and Join Strategy for Solving Constraint Satisfaction Problems. MICAI (Special Sessions) 2015: 73-79 - [c56]José Carlos Ortiz-Bayliss
Lifelong Learning Selection Hyper-heuristics for Constraint Satisfaction Problems. MICAI (1) 2015: 190-201 - [p5]Jorge Alberto Soria-Alcaraz, Juan Martín Carpio Valadez
Parallel Meta-heuristic Approaches to the Course Timetabling Problem. Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization 2015: 391-417 - 2014
- [j5]Eunice López-Camacho, Hugo Terashima-Marín
A unified hyper-heuristic framework for solving bin packing problems. Expert Syst. Appl. 41(15): 6876-6889 (2014) - [c55]Edgar Reyna-Ayala, Santiago E. Conant-Pablos
Assembling Similar Tracking Approaches in Order to Strengthen Performance. MCPR 2014: 201-210 - [p4]Jorge Alberto Soria-Alcaraz, Juan Martín Carpio
Generic Memetic Algorithm for Course Timetabling ITC2007. Recent Advances on Hybrid Approaches for Designing Intelligent Systems 2014: 481-492 - 2013
- [j4]Eunice López-Camacho
An effective heuristic for the two-dimensional irregular bin packing problem. Ann. Oper. Res. 206(1): 241-264 (2013) - [j3]José Carlos Ortiz-Bayliss
Learning vector quantization for variable ordering in constraint satisfaction problems. Pattern Recognit. Lett. 34(4): 423-432 (2013) - [c54]Alejandro Sosa-Ascencio, Hugo Terashima-Marín
Grammar-based Genetic Programming for evolving variable ordering heuristics. IEEE Congress on Evolutionary Computation 2013: 1154-1161 - [c53]Eunice López-Camacho
Evolving feature selection for characterizing and solving the 1D and 2D bin packing problem. IEEE Congress on Evolutionary Computation 2013: 2094-2101 - [c52]José Carlos Ortiz-Bayliss
Using learning classifier systems to design selective hyper-heuristics for constraint satisfaction problems. IEEE Congress on Evolutionary Computation 2013: 2618-2625 - [c51]José Carlos Ortiz-Bayliss
Exploring heuristic interactions in constraint satisfaction problems: A closer look at the hyper-heuristic space. IEEE Congress on Evolutionary Computation 2013: 3307-3314 - [c50]José Carlos Ortiz-Bayliss
A Supervised Learning Approach to Construct Hyper-heuristics for Constraint Satisfaction. MCPR 2013: 284-293 - [c49]Adriana Perez-Lopez, Rosario Baltazar
Homogeneous Population Solving the Minimal Perturbation Problem in Dynamic Scheduling of Surgeries. MICAI (1) 2013: 473-484 - [c48]José Carlos Ortiz-Bayliss
Automatic Generation of Heuristics for Constraint Satisfaction Problems. NICSO 2013: 315-327 - [c47]José Carlos Ortiz-Bayliss
Branching Schemes and Variable Ordering Heuristics for Constraint Satisfaction Problems: Is There Something to Learn? NICSO 2013: 329-342 - [c46]José Carlos Ortiz-Bayliss
A genetic programming hyper-heuristic: Turning features into heuristics for constraint satisfaction. UKCI 2013: 183-190 - [p3]Jorge Alberto Soria-Alcaraz, Juan Martín Carpio, Héctor Puga, Hugo Terashima-Marín, Laura Cruz Reyes, Marco Aurelio Sotelo-Figueroa:
Methodology of Design: A Novel Generic Approach Applied to the Course Timetabling Problem. Soft Computing Applications in Optimization, Control, and Recognition 2013: 287-319 - 2012
- [j2]Juan-Carlos Gomez, Hugo Terashima-Marín:
Construyendo híper-heurísticas generales para problemas de corte multi-objetivo. Computación y Sistemas 16(3) (2012) - [c45]Jorge Humberto Moreno-Scott, José Carlos Ortiz-Bayliss
Challenging heuristics: evolving binary constraint satisfaction problems. GECCO 2012: 409-416 - [c44]José Carlos Ortiz-Bayliss
Improving the performance of vector hyper-heuristics through local search. GECCO 2012: 1269-1276 - [c43]Eunice López-Camacho
The impact of the bin packing problem structure in hyper-heuristic performance. GECCO (Companion) 2012: 1545-1546 - [c42]Alejandro Sosa-Ascencio, Manuel Valenzuela-Rendón, Hugo Terashima-Marín
Cooperative Coevolution of Automatically Defined Functions with Gene Expression Programming. MICAI (Special Sessions) 2012: 89-94 - [c41]Alan I. Torres-Nogales, Santiago E. Conant-Pablos
Local Features Classification for Adaptive Tracking. MICAI (1) 2012: 146-157 - [c40]Dulce J. Magaña-Lozano, Santiago E. Conant-Pablos
Exploring the Solution of Course Timetabling Problems through Heuristic Segmentation. MICAI (1) 2012: 347-358 - 2011
- [c39]Santiago Enrique Conant-Pablos
Evolving solutions of mixed-model assembly line balancing problems by chaining heuristic optimization methods: track: evolutionary combinatorial optimization and meta-heuristics. GECCO (Companion) 2011: 49-50 - [c38]José Carlos Ortiz-Bayliss
On the idea of evolving decision matrix hyper-heuristics for solving constraint satisfaction problems. GECCO (Companion) 2011: 255-256 - [c37]Eunice López-Camacho
A hyper-heuristic for solving one and two-dimensional bin packing problems. GECCO (Companion) 2011: 257-258 - [c36]José Carlos Ortiz-Bayliss
Evolution of neural networks topologies and learning parameters to produce hyper-heuristics for constraint satisfaction problems. GECCO (Companion) 2011: 261-262 - [c35]José Carlos Ortiz-Bayliss
Neural Networks to Guide the Selection of Heuristics within Constraint Satisfaction Problems. MCPR 2011: 250-259 - [c34]José Carlos Ortiz-Bayliss
Variable and Value Ordering Decision Matrix Hyper-heuristics: A Local Improvement Approach. MICAI (1) 2011: 125-136 - [p2]Santiago E. Conant-Pablos, Rolando R. Hernández-Cisneros, Hugo Terashima-Marín:
Feature Selection for the Classification of Microcalcifications in Digital Mammograms using Genetic Algorithms, Sequential Search and Class Separability. Genetic and Evolutionary Computation: Medical Applications 2011 - [p1]Jorge Alberto Soria-Alcaraz, Juan Martín Carpio Valadez
Academic Timetabling Design Using Hyper-Heuristics. Soft Computing for Intelligent Control and Mobile Robotics 2011: 43-56 - 2010
- [j1]Hugo Terashima-Marín
Generalized hyper-heuristics for solving 2D Regular and Irregular Packing Problems. Ann. Oper. Res. 179(1): 369-392 (2010) - [c33]José Carlos Ortiz-Bayliss
Mapping the performance of heuristics for Constraint Satisfaction. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c32]Eunice López-Camacho
Problem-state representations in a hyper-heuristic approach for the 2D irregular BPP. GECCO 2010: 297-298 - [c31]Eunice López-Camacho
Defining a Problem-State Representation with Data Mining within a Hyper-heuristic Model Which Solves 2D Irregular Bin Packing Problems. IBERAMIA 2010: 204-213 - [c30]Juan-Carlos Gomez
Approximating Multi-Objective Hyper-Heuristics for Solving 2D Irregular Cutting Stock Problems. MICAI (2) 2010: 349-360
2000 – 2009
- 2009
- [c29]José Abdón Ramírez-Ruiz, Manuel Valenzuela-Rendón, Hugo Terashima-Marín
uQFCS: QFCS with unfixed fuzzy sets in continuous multi-step environments with continuous vector actions. GECCO 2009: 1307-1314 - [c28]José Carlos Ortiz-Bayliss
A neuro-evolutionary approach to produce general hyper-heuristics for the dynamic variable ordering in hard binary constraint satisfaction problems. GECCO 2009: 1811-1812 - [c27]Santiago E. Conant-Pablos
Pipelining Memetic Algorithms, Constraint Satisfaction, and Local Search for Course Timetabling. MICAI 2009: 408-419 - 2008
- [c26]Hugo Terashima-Marín
Hyper-heuristics for the dynamic variable ordering in constraint satisfaction problems. GECCO 2008: 571-578 - [c25]José Abdón Ramírez-Ruiz, Manuel Valenzuela-Rendón, Hugo Terashima-Marín
A new approach to fuzzy LCSs in two-dimensional continuous multistep environment with continuous vector actions. GECCO 2008: 1433-1434 - [c24]Hugo Terashima-Marín, José Carlos Ortiz-Bayliss, Peter Ross, Manuel Valenzuela-Rendón:
Using Hyper-heuristics for the Dynamic Variable Ordering in Binary Constraint Satisfaction Problems. MICAI 2008: 407-417 - [c23]José Abdón Ramírez-Ruiz, Manuel Valenzuela-Rendón, Hugo Terashima-Marín
QFCS: A Fuzzy LCS in Continuous Multi-step Environments with Continuous Vector Actions. PPSN 2008: 286-295 - [c22]Luis M. Fernandez-Carrasco, Hugo Terashima-Marín
On the possibility to design intelligent sensor systems after excitable media models: An agent-based simulation. SMC 2008: 1181-1186 - 2007
- [c21]Carlos D. Toledo-Suárez, Manuel Valenzuela-Rendón, Hugo Terashima-Marín
On the relativity in the assessment of blind optimization algorithms and the problem-algorithm coevolution. GECCO 2007: 1436-1443 - [c20]Hugo Terashima-Marín
Comparing two models to generate hyper-heuristics for the 2d-regular bin-packing problem. GECCO 2007: 2182-2189 - [c19]Rolando R. Hernández-Cisneros, Hugo Terashima-Marín
Comparison of Class Separability, Forward Sequential Search and Genetic Algorithms for Feature Selection in the Classification of Individual and Clustered Microcalcifications in Digital Mammograms. ICIAR 2007: 911-922 - 2006
- [c18]Rolando R. Hernández-Cisneros, Hugo Terashima-Marín:
Evolutionary Neural Networks Applied To The Classification Of Microcalcification Clusters In Digital Mammograms. IEEE Congress on Evolutionary Computation 2006: 2459-2466 - [c17]Hugo Terashima-Marín
A GA-based method to produce generalized hyper-heuristics for the 2D-regular cutting stock problem. GECCO 2006: 591-598 - [c16]Hugo Terashima-Marín
Two-Phase GA-Based Model to Learn Generalized Hyper-heuristics for the 2D-Cutting Stock Problem. IBERAMIA-SBIA 2006: 198-207 - [c15]Emmanuel Martinez
Assessing the Value of Future and Present Options in Real-Time Planning. IBERAMIA-SBIA 2006: 522-531 - [c14]Rolando R. Hernández-Cisneros, Hugo Terashima-Marín:
Classification of Individual and Clustered Microcalcifications in Digital Mammograms Using Evolutionary Neural Networks. MICAI 2006: 1200-1210 - 2005
- [c13]Hugo Terashima-Marín, Armando Moran-Saavedra, Peter Ross:
Forming hyper-heuristics with GAs when solving 2D-regular cutting stock problems. Congress on Evolutionary Computation 2005: 1104-1110 - [c12]Hugo Terashima-Marín
Hyper-heuristics and classifier systems for solving 2D-regular cutting stock problems. GECCO 2005: 637-643 - [c11]Samuel Oporto-Díaz
Detection of Microcalcification Clusters in Mammograms Using a Difference of Optimized Gaussian Filters. ICIAR 2005: 998-1005 - [c10]Alberto Cuesta-Cañada, Leonardo Garrido, Hugo Terashima-Marín
Building Hyper-heuristics Through Ant Colony Optimization for the 2D Bin Packing Problem. KES (4) 2005: 654-660 - [c9]Hugo Terashima-Marín
Scheduling Transportation Events with Grouping Genetic Algorithms and the Heuristic DJD. MICAI 2005: 185-194 - [c8]Manuel Valenzuela-Rendón, Horacio Martinez-Alfaro, Hugo Terashima-Marín
A Deterministic Alternative to Competent Genetic Algorithms That Solves to Optimality Linearly Decomposable Non-overlapping Problems in Polynomial Time. MICAI 2005: 692-701 - [e1]Alexander F. Gelbukh
MICAI 2005: Advances in Artificial Intelligence, 4th Mexican International Conference on Artificial Intelligence, Monterrey, Mexico, November 14-18, 2005, Proceedings. Lecture Notes in Computer Science 3789, Springer 2005, ISBN 3-540-29896-7 [contents] - 2004
- [c7]Daniel Ángel Huerta-Amante, Hugo Terashima-Marín
Adaptive Penalty Weights When Solving Congress Timetabling. IBERAMIA 2004: 144-153 - [c6]Manuel Iván Angles-Domínguez, Hugo Terashima-Marín
Stability Analysis for Dynamic Constraint Satisfaction Problems. MICAI 2004: 169-178 - 2003
- [c5]Stephan Dempe
Application of Discrete Bilevel Programming to Some Applied Problems. ENC 2003: 254-262 - 2002
- [c4]Sergio Daniel Montaño-Marañón, Hugo Terashima-Marín:
Optimizing Weight and Torque of Squirrel-Cage Induction Motors Using Genetic Algorithms. GECCO Late Breaking Papers 2002: 343-350
1990 – 1999
- 1999
- [c3]Hugo Terashima-Marín
Application of the hardness theory when solving the timetabling problem with genetic algorithms. CEC 1999: 604-611 - [c2]Hugo Terashima-Marín
Clique-based crossover for solving the timetabling problem with GAs. CEC 1999: 1200-1206 - 1995
- [c1]Peter Ross, David Corne, Hugo Terashima-Marín
The Phase-Transition Niche for Evolutionary Algorithms in Timetabling. PATAT 1995: 309-324
Coauthor Index
Iván Amaya
aka: Ivan M. Amaya-Contreras
aka: Ivan M. Amaya-Contreras
Santiago E. Conant-Pablos
aka: Santiago Enrique Conant-Pablos
aka: Santiago Enrique Conant-Pablos
[j33] [j31] [j29] [c79] [c78] [j27] [c77] [i6] [j23] [j22] [j20] [j19] [c76] [i5] [j18] [j17] [c75] [c74] [c73] [c72] [c71] [c70] [i4] [i3] [j16] [j15] [c69] [c68] [c67] [j13] [j12] [c65] [c64] [i1] [c63] [c62] [c61] [c60] [j9] [j8] [j7] [c59] [c58] [c57] [c56] [j3] [c52] [c51] [c50] [c48] [c47] [c46] [c45] [c44] [c38] [c36] [c35] [c34] [c33] [c28] [c26] [c24]
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last updated on 2024-12-12 21:55 CET by the dblp team
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