Publications
Thesis
S. Zapotecas-Martínez (2013), Nongradient Mathematical Programming Techniques Used to Improve Multi-Objective Evolutionary Algorithms, PhD Thesis, CINVESTAV-IPN, Mexico city, MEXICO, June, 2013.
Books
K. Miranda, A. García-Nájera, and S. Zapotecas-Martínez (2024). “Pensamiento Algorítmico”. Universidad Autónoma Metropolitana. ISBN: 978-607-28-3140-7.
A. Menchaca-Méndez, S. Zapotecas-Martínez, E. Montero, C. A. Coello Coello, K. Rodríguez Vázquez, and S. R. Tinoco Martínez (2020). “Prácticas didácticas para el estudio y comprención de metaheurísticas utilizadas en la resolución de problemas de optimización difíciles”. Universidad Nacional Auntónoma de México. URL: https://www.innovacioneducativa.unam.mx:8443/jspui/handle/123456789/7455.
Book Chapters
L. Pérez-Enriquéz, M. A. Jiménez-Domínguez, N. A. García-Rojas, R. Solar-Hernández, S. Zapotecas-Martínez, and L. Altamirano-Robles (2024). “Image Contrast Enhancement: Harnessing Metaheuristics and the Gaussian Error Function”. In: Advances in Optimization Algorithms for Multidisciplinary Engineering Applications: From Classical Methods to AI-Enhanced Solutions. Springer. (To appear)
2. K. Miranda, S. Zapotecas-Martínez, A. López-Jaimes, and A. García-Nájera (2019). “A Comparison of Bio-Inspired Approaches for the Cluster-Head Selection Problem in WSN”. In: Advances in Nature-Inspired Computing and Applications. Ed. by S. K. Shandilya, S. Shandilya, and A. K. Nagar. Springer, CHAP. 7, pp. 165–187. ISBN: 978-3-319-96450-8.
S. Zapotecas-Martínez, A. Lara, and C. A. Coello Coello (2017). “Hybridizing MOEAs with Mathematical-Programming Techniques”. In: Decision Sciences. Theory and Practice. Ed. by R. N. Sengupta, A. Gupta, and J. Dutta. CRC Press. Taylor & Francis Group, CHAP. 4, pp. 185–232. ISBN: 9781482282566.
A. López Jaimes, S. Zapotecas Martínez, and C. A. Coello Coello (2011). “An Introduction to Multiobjective Optimization Techniques”. In: Optimization in Polymer Processing. Ed. by A. Gaspar-Cunha and J. A. Covas. Nova Science Publishers, CHAP. 3, pp. 29–57. ISBN: 978-1-61122-818-2.
Peer-reviewed Journal Papers
L. A. Beltran, M. A. Navarro, D. Oliva, D. Campos-Peña, J. A. Ramos-Frutos, and S. Zapotecas-Martínez (2024). “Quasirandom Fractal Search (QRFS): A dynamic metaheuristic with sigmoid population decrement for global optimization”. Expert Systems with Applications, VOL. 254, pp. 124400. ISSN: 0957-4174. DOI: https://doi.org/10.1016/j.eswa.2024.124400.
I. Miguel-Andrés, J. Ramos-Frutos, M. Sharawi, D. Oliva, E. Reyes-Dávila, A. Casas-Ordaz, M. Pérez-Cisneros, and S. Zapotecas-Martínez (2024). “Wrapper-based feature selection to classify flatfoot disease”. IEEE Access, VOL. 12, pp. 22433–22447. ISSN: 2169-3536. DOI: https://doi.org/10.1109/ACCESS.2024.3361936.
S. Zapotecas-Martínez, R. Armas, and A. García-Nájera (2024). “A multi-objective evolutionary approach for the electric vehicle charging stations problem”. Expert Systems with Applications, VOL. 240, pp. 122514. ISSN: 0957-4174. DOI: https://doi.org/10.1016/j.eswa.2023.122514.
S. Zapotecas-Martínez, A. García-Nájera, and A. Menchaca-Méndez (2023). “Engineering applications of multi-objective evolutionary algorithms: A test suite of box-constrained real-world problems”. Engineering Applications of Artificial Intelligence, VOL. 123, pp. 106192. ISSN: 0952-1976. DOI: https://doi.org/10.1016/j.engappai.2023.106192.
S. Zapotecas-Martínez, C. A. Coello Coello, H. E. Aguirre, and K. Tanaka (2023). “Challenging test problems for multi- and many-objective optimization”. Swarm and Evolutionary Computation, VOL. 81, pp. 101350. ISSN: 2210-6502. DOI: https://doi.org/10.1016/j.swevo.2023.101350.
A. Menchaca-Méndez, S. Zapotecas-Martínez, L. M. García-Velázquez, and C. A. Coello Coello (2022). “Uniform Mixture Design via Evolutionary Multi-Objective Optimization”. Swarm and Evolutionary Computation, VOL. 68, pp. 100979. ISSN: 2210-6502. DOI: https://doi.org/10.1016/j.swevo.2021.100979.
S. Zapotecas-Martínez, A. García-Nájera, and A. Menchaca-Méndez (2022). “Improved Lebesgue Indicator-Based Evolutionary Algorithm: Reducing Hypervolume Computations”. Mathematics, VOL. 10, NUM. 1, pp. 19. ISSN: 2227–7390. DOI: https://doi.org/10.3390/math10010019.
V. Escandon-Bailon, H. Cervantes, A. García-Nájera, and S. Zapotecas-Martínez (2021). “Analysis of the multi-objective release plan rescheduling problem”. Knowledge-Based Systems, pp. 106922. ISSN: 0950-7051. DOI: https://doi.org/10.1016/j.knosys.2021.106922.
A. García-Nájera, S. Zapotecas-Martínez, and K. Miranda (2021). “Analysis of the multi-objective cluster head selection problem in WSNs”. Applied Soft Computing, pp. 107853. ISSN: 1568-4946. DOI: https://doi.org/10.1016/j.asoc.2021.107853.
O. Cuate, A. Ponsich, L. Uribe, S. Zapotecas-Martínez, A. Lara, and O. Schütze (2020). “A New Hybrid Evolutionary Algorithm for the Treatment of Equality Constrained MOPs”. Mathematics, VOL. 1, NUM. 8, pp. 7. ISSN: 2227–7390. DOI: https://doi.org/10.3390/math8010007.
A. Menchaca-Méndez, E. Montero, L. Miguel, S. Zapotecas-Martínez, C. A. Coello Coello, and M.-C. Riff (2019). “A Coevolutionary Scheme for Multi-Objective Evolutionary Algorithms based on -dominance”. IEEE Access, VOL. 7, pp. 18267–18283. ISSN: 2169-3536. DOI: https://doi.org/10.1109/ACCESS.2019.2896962.
S. Zapotecas-Martínez, C. A. Coello Coello, H. E. Aguirre, and K. Tanaka (2019). “A Review of Features and Limitations of Existing Scalable Multiobjective Test Suites”. IEEE Transactions on Evolutionary Computation, VOL. 23, NUM. 1, pp. 130–142. ISSN: 1089-778X. DOI: https://doi.org/10.1109/TEVC.2018.2836912.
S. Zapotecas-Martínez, A. García-Nájera, and A. López-Jaimes (2019). “LIBEA: A Lebesgue Indicator-Based Evolutionary Algorithm for multi-objective optimization”. Swarm and Evolutionary Computation, VOL. 44, pp. 404–419. ISSN: 2210-6502. DOI: https://doi.org/10.1016/j.swevo.2018.05.004.
S. Zapotecas-Martínez, A. García-Nájera, and A. López-Jaimes (2019). “Multi-objective grey wolf optimizer based on decomposition”. Expert Systems with Applications, VOL. 120, pp. 357–371. ISSN: 0957-4174. DOI: https://doi.org/10.1016/j.eswa.2018.12.003.
S. Alvarado, C. Segura, O. Schütze, and S. Zapotecas (2018). “The Gradient Subspace Approximation as Local Search Engine within Evolutionary Multi-objective Optimization Algorithms”. Computación y Sistemas, VOL. 22, NUM. 2, pp. 363–385. ISSN: 2007-9737. https://doi.org/10.13053/CyS-22-2-2948.
A. Menchaca-Méndez, E. Montero, and S. Zapotecas-Martínez (2018). “An Improved S-Metric Selection Evolutionary Multi-Objective Algorithm with Adaptive Resource Allocation”. IEEE Access, VOL. 6, pp. 63382–63401. ISSN: 2169-3536. DOI: https://doi.org/10.1109/ACCESS.2018.2877402.
S. Zapotecas-Martínez and C. A. Coello Coello (2016). “MONSS: A multi-objective nonlinear simplex search approach”. Engineering Optimization, VOL. 48, NUM. 1, pp. 16–38. ISSN: 0305-215X. DOI: https://doi.org/10.1080/0305215X.2014.992889.
Peer-reviewed International Conference Papers
A. E. P. Castillo, L. A. N. Lázaro, D. F. R. Camera, R. Díaz-Hernández, L. Altamirano-Robles, S. Zapotecas-Martínez, and S. E. A. Raggi (2024). “Improving COVID-19 Recognition: A Study of Contrast Enhancement Techniques and Normalization in Chest X-Rays Images”. In: IEEE 37th International Symposium on Computer Based Medical Systems (CBMS’2024). IEEE Press, (To appear).
O. Ramos-Soto, A. C. Ordaz, D. Oliva, S. E. Balderas-Mata, and S. Zapotecas-Martínez (2024). “Enhancing Retinal OCT Scans via Metaheuristic-Driven Bayesian Speckle Denoising”. In: IEEE 37th International Symposium on Computer Based Medical Systems (CBMS’2024). IEEE Press, (To appear).
M. A. Jiménez-Domínguez, N. A. García-Rojas, S. Zapotecas-Martínez, R. D. Hernández, and L. Altamirano-Robles (2024). “Exploring multi-objective evolutionary approaches for path planning of autonomous mobile robots”. In: 2024 IEEE Congress on Evolutionary Computation (CEC). IEEE Press, (To Appear).
A. Valdivia, I. Aranguren, J. Ramos-Frutos, A. Casas-Ordaz, D. Oliva, and S. Zapotecas-Martínez (2024). “Improved Golden Sine II in Synergy with Non-monopolized Local Search Strategy”. In: Metaheuristics (MIC’2024). Springer Nature Switzerland, pp. 279–291. DOI: https://doi.org/10.1007/978-3-031-62922-8_19.
E. M. Ceja-Cruz, A. Menchaca-Méndez, E. Montero, and S. Zapotecas-Martínez (2023). “An Archive-Based Multi-Objective Simulated Annealing Algorithm for the Time/Weight-Balanced Cluster Problem in Delivery Logistics”. In: 2023 IEEE Congress on Evolutionary Computation (CEC). IEEE Press, pp. 1–8. DOI: https://doi.org/10.1109/CEC53210.2023.10253992.
L. Pérez-Enríquez, S. Zapotecas-Martínez, D. Oliva, and L. Altamirano-Robles (2023). “Hyperbolic tangent sigmoid as a transformation function for image contrast enhancement”. In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE Press, pp. 282–287. DOI: https://doi.org/10.1109/SSCI52147.2023.10371971.
J. G. Falcón-Cardona, S. Zapotecas-Martínez, and A. García-Nájera (2021). “Pareto compliance from a practical point of view”. In: Genetic and Evolutionary Computation Conference (GECCO’21). ACM Press, pp. 395–402. DOI: https://doi.org/10.1145/3449639.3459276.
A. García-Nájera, S. Zapotecas-Martínez, J. G. Falcón-Cardona, and H. Cervantes (2021). “Multi-objective release plan rescheduling in agile software development”. In: Mexican International Conference on Artificial Intelligence (MICAI’2021). Springer, pp. 403–414. Best Paper Award. DOI: https://doi.org/10.1007/978-3-030-89817-5_30.
H. M. Maldonado and S. Zapotecas-Martínez (2021). “A Dynamic Penalty Function within MOEA/D for Constrained Multiobjective Optimization Problems”. In: 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE Press, pp. 1470–1477. DOI: https://doi.org/10.1109/CEC45853.2021.9504940.
A. García-Nájera, S. Zapotecas-Martínez, and R. Bernal-Jaquez (2020). “Selection Schemes Analysis in Genetic Algorithms for the Maximum Influence Problem”. In: Mexican International Conference on Artificial Intelligence (MICAI'2020). Springer, pp. 211–222. DOI: https://doi.org/10.1007/978-3-030-60884-2_16.
S. Zapotecas-Martínez, A. García-Nájera, and H. Cervantes (2020). “Multi-objective Optimization in the Agile Software Project Scheduling using Decomposition”. In: Genetic and Evolutionary Computation Conference Companion (GECCO’20 Companion). ACM Press, pp. 1495–1502. DOI: https://doi.org/10.1145/3377929.3398146.
S. Zapotecas-Martínez and A. Menchaca-Méndez (2020). “On the Performance of Generational and Steady-State MOEA/D in the Multi-Objective 0/1 Knapsack Problem”. In: 2020 IEEE Congress on Evolutionary Computation (CEC). IEEE Press, pp. 1–8. DOI: https://doi.org/10.1145/3377929.3398146.
S. Zapotecas-Martínez and A. Ponsich (2020). “Constraint Handling within MOEA/D Through an Additional Scalarizing Function”. In: Genetic and Evolutionary Computation Conference (GECCO’20). ACM Press, pp. 595–602. DOI: https://doi.org/10.1145/3377930.3390240.
Y. Marca, H. Aguirre, S. Zapotecas, A. Liefooghe, B. Derbel, S. Verel, and K. Tanaka (2019). “Approximating Pareto Set Topology by Cubic Interpolation on Bi-objective Problems”. In: International Conference on Evolutionary Multi-Criterion Optimization. Springer, pp. 386–398. Best Paper Award. DOI: https://doi.org/10.1007/978-3-030-12598-1_31.
A. Rodríguez Sánchez, A. Ponsich, A. López Jaimes, and S. Zapotecas Martínez (2019). “A parallel Tabu Search heuristic to approximate Uniform Designs for reference set based MOEAs”. In: International Conference on Evolutionary Multi-Criterion Optimization. Springer, pp. 254–265. DOI: https://doi.org/10.1007/978-3-030-12598-1_21.
Y. Marca, H. Aguirre, S. Zapotecas, A. Liefooghe, B. Derbel, S. Verel, and K. Tanaka (2018). “Pareto Dominance-based MOEAs on Problems with Difficult Pareto Set Topologies”. In: GECCO (Companion). ACM Press, pp. 189–190. DOI: https://doi.org/10.1145/3205651.3205746.
E. Montero and S. Zapotecas-Martínez (2018). “An Analysis of Parameters of Decomposition-Based MOEAs on Many-Objective Optimization”. In: 2018 IEEE Congress on Evolutionary Computation (CEC’2018). IEEE Press, pp. 1–8. DOI: https://doi.org/10.1109/CEC.2018.8477648.
S. Zapotecas-Martínez, A. López-Jaimes, K. Miranda, and A. García-Nájera (2018). “Decomposition-based Multi-Objective Evolutionary Optimization for Cluster-Head Selection in WSNs”. In: 2018 IEEE Congress on Evolutionary Computation (CEC’2018). IEEE Press, pp. 1–8. DOI: https://doi.org/10.1109/CEC.2018.8477778.
A. García-Nájera, A. López-Jaimes, and S. Zapotecas-Martínez (2017). “On the Many-Objective Pickup and Delivery Problem: Analysis of the Performance of Three Evolutionary Algorithms”. In: Mexican International Conference on Artificial Intelligence. Springer, pp. 69–81. Best Paper Award. DOI: https://doi.org/10.1007/978-3-030-02837-4_6.
W. Ren Tan, S. Zapotecas-Martínez, H. E. Aguirre, and K. Tanaka (2016). “A Refinement Mechanism to Improve Particle Swarm Optimization”. In: 2016 IEEE Congress on Evolutionary Computation (CEC’2016). IEEE Press, pp. 2049–2056. DOI: https://doi.org/10.1109/CEC.2016.7744040.
S. Zapotecas-Martínez, S. Jacquin, H. E. Aguirre, and K. Tanaka (2016). “Analysis and Comparison of Multi-objective Evolutionary Approaches on the Multi-Objective 1/0 Unit Commitment Problem”. In: 2016 IEEE Congress on Evolutionary Computation (CEC’2016). IEEE Press, pp. 3019–3026. DOI: https://doi.org/10.1109/CEC.2016.7744171.
S. Zapotecas-Martínez, A. Moraglio, H. E. Aguirre, and K. Tanaka (2016). “Geometric Particle Swarm Optimization for Multi-objective Optimization Using Decomposition”. In: Proceedings of the 18th annual conference on Genetic and Evolutionary Computation (GECCO’2016). ACM Press, pp. 69–76. DOI: https://doi.org/10.1145/2908812.2908880.
H. E. Aguirre, S. Zapotecas-Martínez, A. Liefooghe, S. Verel, and K. Tanaka (2015). “Approaches for Many-objective Optimization: Analysis and Comparison on MNK-landscapes”. In: Artificial Evolution - 12th International Conference, Evolution Artificielle, EA 2015. Springer, pp. 14–28. DOI: https://doi.org/10.1007/978-3-319-31471-6_2.
R. Armas, H. E. Aguirre, S. Zapotecas-Martínez, and K. Tanaka (2015). “Traffic Signal Optimization: Minimizing Travel Time and Fuel Consumption”. In: Artificial Evolution - 12th International Conference, Evolution Artificielle, EA 2015. Springer, pp. 29–43. DOI: https://doi.org/10.1007/978-3-319-31471-6_3.
T. Yeoh, S. Zapotecas-Martínez, Y. Akimoto, H. Aguirre, and K. Tanaka (2015). “Feature Selection in Gait Classification using Geometric PSO Assisted by SVM”. In: 16th International Conference on Computer Analysis of Images and Patterns (CAIP’2015). Springer, pp. 566–578. DOI: https://doi.org/10.1007/978-3-319-23117-4_49.
S. Zapotecas-Martínez, H. E. Aguirre, K. Tanaka, and C. A. Coello Coello (2015). “On the Low-Dyscrepancy Sequences and Their use in MOEA/D for High-Dimensional Objective Spaces”. In: 2015 IEEE Congress on Evolutionary Computation (CEC’2015). IEEE Press, pp. 2835–2842. DOI: https://doi.org/10.1109/CEC.2015.7257241.
S. Zapotecas-Martínez, B. Derbel, A. Liefooghe, H. E. Aguirre, and K. Tanaka (2015). “Geometric Differential Evolution in MOEA/D: A Preliminary Study”. In: Mexican International Conference on Artificial Intelligence (MICAI’2015). Springer, pp. 364–376. DOI: https://doi.org/10.1007/978-3-319-27060-9_30.
S. Zapotecas-Martínez, B. Derbel, A. Liefooghe, D. Brockhoff, H. E. Aguirre, and K. Tanaka (2015). “Injecting CMA-ES into MOEA/D”. In: Proceedings of the 17th annual conference on Genetic and Evolutionary Computation (GECCO’2015). ACM Press, pp. 783–790. DOI: https://doi.org/10.1145/2739480.2754754.
T. Yeoh, S. Zapotecas Martínez, Y. Akimoto, H. E. Aguirre, and K. Tanaka (2014). “Genetic Algorithm Assisted by a SVM for Feature Selection in Gait Classification”. In: 2014 IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS’2014). IEEE Press, pp. 191–195. DOI: https://doi.org/10.1109/ISPACS.2014.7024450.
S. Zapotecas Martínez, A. Arias Montaño, and C. A. Coello Coello (2014). “Constrained Multi-Objective Aerodynamic Shape Optimization via Swarm Intelligence”. In: Proceedings of the 16th annual conference on Genetic and Evolutionary Computation (GECCO’2014). ACM Press, pp. 81–88. DOI: https://doi.org/10.1145/2576768.2598372.
S. Zapotecas Martínez and C. A. Coello Coello (2014). “A Multi-objective Evolutionary Algorithm based on Decomposition for Constrained Multi-objective Optimization”. In: 2014 IEEE Congress on Evolutionary Computation (CEC’2014). IEEE Press, pp. 429–436. DOI: https://doi.org/10.1109/CEC.2014.6900645.
S. Zapotecas Martínez, V. A. Sosa Hernández, H. E. Aguirre, K. Tanaka, and C. A. Coello Coello (2014). “Using a Family of Curves to Approximate the Pareto Front of a Multi-Objective Optimization Problem”. In: Parallel Problem Solving from Nature–PPSN XIII. Springer, pp. 682–691. DOI: https://doi.org/10.1007/978-3-319-10762-2_67.
S. Zapotecas Martínez and C. A. Coello Coello (2013). “A Hybridization of MOEA/D with the Nonlinear Simplex Search Algorithm”. In: 2013 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM’2013). IEEE Press, pp. 48–55. DOI: https://doi.org/10.1109/MCDM.2013.6595443.
S. Zapotecas Martínez and C. A. Coello Coello (2013). “Combining Surrogate Models and Local Search for Dealing with Expensive Multi-objective Optimization Problems”. In: 2013 IEEE Congress on Evolutionary Computation (CEC’2013). IEEE Press, pp. 2572–2579. DOI: https://doi.org/10.1109/CEC.2013.6557879.
S. Zapotecas Martínez and C. A. Coello Coello (2013). “MOEA/D assisted by RBF Networks for Expensive Multi-Objective Optimization Problems”. In: Proceedings of the 15th annual conference on Genetic and Evolutionary Computation (GECCO’2013). ACM Press, pp. 1405–1412. DOI: https://doi.org/10.1145/2463372.2465805.
S. Roy, S. Zapotecas Martínez, C. A. Coello Coello, and S. Sengupta (2012). “A Multi-Objective Evolutionary Approach for Linear Antenna Array Design and Synthesis”. In: 2012 IEEE Congress on Evolutionary Computation (CEC’2012). IEEE Press, pp. 3423–3430. DOI: https://doi.org/10.1109/CEC.2012.6252989.
S. Roy, S. Zapotecas Martínez, C. A. Coello Coello, and S. Sengupta (2012). “Adaptive IIR System Identification using JADE”. In: World Automation Congress 2012 (WAC’2012). IEEE Press, pp. 1–6. URL: https://ieeexplore.ieee.org/abstract/document/6320967.
S. Zapotecas Martínez and C. A. Coello Coello (2012). “A Direct Local Search Mechanism for Decomposition-based Multi-Objective Evolutionary Algorithms”. In: 2012 IEEE Congress on Evolutionary Computation (CEC’2012). IEEE Press, pp. 3431–3438. DOI: https://doi.org/10.1109/CEC.2012.6252990.
S. Zapotecas Martínez, A. Arias Montaño, and C. A. Coello Coello (2011). “A Nonlinear Simplex Search Approach for Multi-Objective Optimization”. In: 2011 IEEE Congress on Evolutionary Computation (CEC’2011). IEEE Press, pp. 2367–2374. DOI: https://doi.org/10.1109/CEC.2011.5949910.
S. Zapotecas Martínez and C. A. Coello Coello (2011). “A Multi-objective Particle Swarm Optimizer Based on Decomposition”. In: Proceedings of the 13th annual conference on Genetic and Evolutionary Computation (GECCO’2011). ACM Press, pp. 69–76. DOI: https://doi.org/10.1145/2001576.2001587.
S. Zapotecas Martínez and C. A. Coello Coello (2011). “Swarm Intelligence Guided by Multi-objective Mathematical Programming Techniques”. In: GECCO (Companion). ACM Press, pp. 771–774. DOI: https://doi.org/10.1145/2001858.2002088.
S. Zapotecas Martínez, E. G. Yáñez Oropeza, and C. A. Coello Coello (2011). “Self-Adaptation Techniques Applied to Multi-Objective Evolutionary Algorithms”. In: Learning and Intelligent Optimization, 5th International Conference, LION 5. Springer, pp. 567–581. DOI: https://doi.org/10.1007/978-3-642-25566-3_44.
S. Zapotecas Martínez and C. A. Coello Coello (2010). “A Memetic Algorithm with Non Gradient-Based Local Search Assisted by a Meta-Model”. In: Parallel Problem Solving from Nature–PPSN XI. Springer, pp. 576–585. DOI: https://doi.org/10.1007/978-3-642-15844-5_58.
S. Zapotecas Martínez and C. A. Coello Coello (2010). “A Multi-Objective Meta-Model Assisted Memetic Algorithm with Non Gradient-Based Local Search”. In: GECCO (Companion). ACM Press, pp. 537–538. DOI: https://doi.org/10.1145/1830483.1830581.
S. Zapotecas Martínez and C. A. Coello Coello (2010). “A Novel Diversification Strategy for Multi-Objective Evolutionary Algorithms”. In: GECCO (Companion). ACM Press, pp. 2031–2034. DOI: https://doi.org/10.1145/1830761.1830852.
S. Zapotecas Martínez and C. A. Coello Coello (2010). “An Archiving Strategy Based on the Convex Hull of Individual Minima for MOEAs”. In: 2010 IEEE Congress on Evolutionary Computation (CEC’2010). IEEE Press, pp. 912–919. DOI: https://doi.org/10.1109/CEC.2010.5586462.
S. Zapotecas Martínez and C. A. Coello Coello (2008). “A Proposal to Hybridize Multi-Objective Evolutionary Algorithms with Non-Gradient Mathematical Programming Techniques”. In: Parallel Problem Solving from Nature–PPSN X. Springer, pp. 837–846. DOI: https://doi.org/10.1007/978-3-540-87700-4_83.
S. Zapotecas Martínez and C. A. Coello Coello (2008). “Hybridizing an Evolutionary Algorithm with Mathematical Programming Techniques for Multi-Objective Optimization”. In: GECCO (Companion). ACM Press, pp. 769–770. DOI: https://doi.org/10.1145/1389095.1389247.
S. Zapotecas-Martínez, C. Mancillas-López, F. Rodríguez-Henríquez, and N. Cruz-Cortés (2006). “Reconfigurable Hardware Implementation of the Lenstra Factorization Algorithm”. In: 2006 3rd International Conference on Electrical and Electronics Engineering (ICEEE’2006). IEEE Press, pp. 1–4. DOI: https://doi.org/10.1109/ICEEE.2006.251939.
Technical Reports
S. Zapotecas Martínez & C.A. Coello Coello (2013), MONSS: A Multi-Objective Nonlinear Simplex Search Algorithm. Evolutionary Computation Group at CINVESTAV, Departamento de Computación, CINVESTAV-IPN, México, Technical Report EVOCINV-01-2013, February, 2013. [URL]
S. Zapotecas Martínez & C.A. Coello Coello (2013), MOEA/D assisted by RBF Networks for Expensive Multi-Objective Optimization Problems. Evolutionary Computation Group at CINVESTAV, Departamento de Computación, CINVESTAV-IPN, México, Technical Report EVOCINV-02-2013, February, 2013. [URL]