Jorge Ramos-Frutos, Angel Casas-Ordaz, Saúl Zapotecas-Martínez, Diego Oliva, Arturo Valdivia-González, Abel García-Nájera, and Marco Pérez-Cisneros (2025). Enhancing multi-objective optimization: A decomposition-based approach using the whale optimization algorithm. Mathematics 13(5):767.
Montes-Orozco, E., Miranda, K., García-Nájera, A., and López-García, J. C. (2024). On the analysis of collaboration networks between industry and academia: The Mexican case of the Innovation Incentive Program. Scientometrics, 129:1523-1544.
Zapotecas-Martínez, S., Armas, R., and García-Nájera, A. (2024). A multi-objective evolutionary approach for the electric vehicle charging stations problem. Expert Systems with Applications, 240:122514.
Zapotecas-Martínez, S., García-Najera, A., and Menchaca-Méndez, A. (2023). Engineering applications of multi-objective evolutionary algorithms: A test suite of box-constrained real-world problems. Engineering Applications of Artificial Intelligence, 123(A):106192.
Zapotecas-Martínez, S., García-Nájera, A., and Menchaca-Méndez, A. (2022). Improved Lebesgue Indicator-Based Evolutionary Algorithm: Reducing Hypervolume Computations. Mathematics, 10(1):19.
García-Nájera, A., Zapotecas-Martínez, S., and Miranda, K. (2021). Analysis of the multi-objective cluster head selection problem in WSNs. Applied Soft Computing, 112:107853.
Escandon-Bailon, V., Cervantes, H., García-Nájera, A. and Zapotecas-Martínez, S. (2021). Analysis of the multi-objective release plan rescheduling problem. Knowledge-Based Systems, 220:106922.
Zapotecas-Martínez, S, García-Nájera, A., and López-Jaimes, A. (2019). Multi-objective grey wolf optimizer based on decomposition. Expert Systems with Applications, 120:357-371. [pdf]
Zapotecas-Martínez, S., López-Jaimes, A., and García-Nájera, A. (2019). LIBEA: A Lebesgue indicator-based evolutionary algorithm for multi-objective optimization. Swarm and Evolutionary Computation, 44:404-419. [pdf]
Vega-Velázquez, M. A., García-Nájera, A., and Cervantes, H. (2018). A survey on the software project scheduling problem. International Journal of Production Economics, 202:145-161. [pdf]
Garcia- Najera, A. and Lopez-Jaimes, A. (2018). An investigation into many-objective optimization on combinatorial problems: analyzing the pickup and delivery problem. Swarm and Evolutionary Computation, 38:218-230. [pdf]
García-Nájera, A., Brizuela, C. A., and Martínez-Pérez, I. M. (2015). An efficient genetic algorithm for setup time minimization in PCB assembly. The International Journal of Advanced Manufacturing Technology, 77(5):973-989. [pdf]
García-Nájera, A., Bullinaria, J. A., and Gutiérrez-Andrade, M. A. (2015). An evolutionary approach for multi-objective vehicle routing problems with backhauls. Computers & Industrial Engineering, 81:90-108. [pdf]
Garcia-Najera, A. and Bullinaria, J.A. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1):287-300. [pdf]
Reyes San Pedro, H., Cervantes Maceda, H., and García Nájera, A. (2021). Identificación de potenciales "hotspots" usando métodos de clasificación. Research in Computing Science, 150(5).
Escandón Bailón, V., Cervantes Maceda, H., and García Nájera, A. (2019). Replaneación de proyectos ágiles de software usando técnicas de optimización. Abstraction & Application, 25: 61-79.
Escandon Bailon, V. H., Cervantes Maceda, H., and García Nájera, A. (2019). Aplicación de un algoritmo genético multiobjetivo para la replaneación de liberaciones en proyectos ágiles de software. Research in Computing Science, 148(8):199-213.
Ledesma Bermúdez, C. I. and García Nájera, A. (2018). Detección de comunidades en redes sociales por medio de un algoritmo de agrupamiento dinámico en alta definición. Research in Computing Science, 147(5):305-318.
Miranda Campos, K. S., López Jaimes, A., and García Nájera, A. (2017). Análisis multiobjetivo de la selección de líderes en redes inalámbricas de sensores. Research in Computing Science, 134:111-125.
Miranda, K., García Nájera, A., and López Jaimes, A. (2017). Algoritmos de autodespliegue para redes de relevos móviles. Revista de Investigación en Tecnologías de la Información, 5(9):77-82.
Camacho Villalón, C. L., García Nájera, A., and Gutiérrez Andrade, M. A. (2016). Algoritmo de optimización mediante forrajeo de bacterias híbrido para el problema de selección de portafolios con restricción de cardinalidad. Research in Computing Science, 116:141-156.
Garcia-Najera, A. and López-Jaimes, A. (2015). The Pickup and Delivery Problem: a Many-objective Analysis. Research in Computing Science, 104:51-60.
Miranda, K., Zapotecas-Martínez, S., López-Jaimes, A., and García-Nájera, A. (2019). A Comparison of Bio-inspired Approaches for the Cluster-Head Selection problem in WSN. In Shandilya S., Shandilya S., Nagar A. (eds) Advances in Nature-inspired Computing and Applications, pp. 165-187. Springer. [pdf]
García Nájera, A., Zapotecas Martínez, S., Falcón Cardona, J. G., and Cervantes, H. (2021). Multi-objective release plan rescheduling in agile software development (Best Paper Award). In: 20th Mexican International Conference on Artificial Intelligence (MICAI 2021), LNAI 13067, pp. 403-414. Springer.
Gómez-Fuentes, M. C., Cervantes, J., and García Nájera, A. (2021), Association and aggregation class relationships: is there a difference in terms of implementation? In: 9th International Conference on Software Engineering Research and Innovation (CONISOFT 2021), pp. 44-53. IEEE.
Falcón-Cardona, J. G., Zapotecas-Martínez, S., and García-Nájera, A. (2021). Pareto compliance from a practical point of view. In: 2021 Genetic and Evolutionary Computation Conference (GECCO 2021), pp. 395-402. ACM.
García-Nájera, A., Zapotecas-Martínez, S., and Bernal-Jaquez, R. (2020). Selection schemes analysis in genetic algorithms for the maximum influence problem. In: 19th Mexican International Conference on Artificial Intelligence (MICAI 2020), LNCS 12468, pp. 211-222. Springer.
Zapotecas-Martínez, S., García-Nájera, A., and Cervantes, H. (2020). Multi-objective optimization in the agile software project scheduling using decomposition. In: 2020 Genetic and Evolutionary Computation Conference Companion (GECCO 2020), pp. 1495–1502. ACM.
García Nájera, A., López Jaimes, A., and Zapotecas Martínez, S. (2018), On the many-objective pickup and delivery problem: Analysis of the performance of three evolutionary algorithms (Best Paper Award). In: 16th Mexican International Conference on Artificial Intelligence (MICAI 2017), LNAI 10632, pp. 69-81. Springer. [pdf]
Zapotecas-Martínez, S., López-Jaimes, A., Miranda, K., and García-Nájera, A. (2018). Decomposition-based Multi-Objective Evolutionary Optimization for Cluster-Head Selection in WSNs. In: 2018 IEEE Congress on Evolutionary Computation (IEEE CEC 2018), pp. 1029-1036. IEEE. [pdf]
López-Jaimes, A. and García-Nájera, A. (2016). Discrete many-objective optimization problems: The case of the pickup and delivery problem. In: 2016 IEEE Congress on Evolutionary Computation (IEEE CEC 2016), pp. 1123-1130. IEEE. [pdf]
Vega, M. A., Cervantes, H., and García, A. (2016). Desarrollo de una herramienta para generar escenarios de planeación de proyectos. In: 4th International Conference on Software Engineering Research and Innovation (CONISOFT 2016), pp. 85-94. [pdf]
García-Nájera, A. and Gómez-Fuentes, M. C. (2014). A Multi-Objective Genetic Algorithm for the Software Project Scheduling Problem. In: 13th Mexican International Conference on Artificial Intelligence (MICAI 2014), LNAI 8857, pp. 13-24. Springer. [pdf]
Garcia-Najera, A. and Gutierrez-Andrade, M.A. (2013). An evolutionary approach to the multi-objective pickup and delivery problem with time windows. In: 2013 IEEE Congress on Evolutionary Computation (IEEE CEC 2013), pp. 997-1004. IEEE. [pdf]
Garcia-Najera, A. (2012). The Vehicle Routing Problem with Backhauls: a Multi-objective Evolutionary Approach. In: 12th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP 2012), LNCS 7245, pp. 255-266. Springer. [pdf]
Garcia-Najera, A. and Bullinaria, J.A. (2010). Optimizing delivery time in multi-objective vehicle routing problems with time windows. In: 11th International Conference on Parallel Problem Solving from Nature (PPSN XI), LNCS 6239, Part II, pp. 51-60. Springer. [pdf]
Garcia-Najera, A. and Bullinaria, J.A. (2009). Comparison of Similarity Measures for the Multi-objective Vehicle Routing Problem with Time Windows. In: Genetic and Evolutionary Computation Conference 2009 (GECCO 2009), pp. 579-586. ACM. [pdf]
Garcia-Najera, A. (2009). Preserving Population Diversity for the Multi-objective Vehicle Routing Problem with Time Windows. In: GECCO 2009 Graduate Student Workshop (GECCO 2009 GSW), pp. 2689-2692. ACM. [pdf]
Garcia-Najera, A. and Bullinaria, J.A. (2009). Bi-objective Optimization for the Vehicle Routing Problem with Time Windows: Using Route Similarity to Enhance Performance. In: 5th International Conference on Evolutionary Multi-Criterion Optimization (EMO'09), LNCS 5467, pp. 275-289. Springer. [pdf]
Garcia-Najera, A. and Brizuela, C.A. (2008). An Efficient Genetic Algorithm for Setup Time Minimization in PCB Assembly. In: VI ALIO/EURO Workshop on Applied Combinatorial Optimization (ALIO/EURO 2008). Universidad de Buenos Aires, Buenos Aires, Argentina. [pdf]
Garcia-Najera, A. and Bullinaria, J.A. (2008). A Multi-Objective Density Restricted Genetic Algorithm for the Vehicle Routing Problem with Time Windows. In: 2008 UK Workshop on Computational Intelligence (UKCI 2008). De Montfort University, Leicester, United Kingdom. [pdf]
Garcia-Najera, A. and Bullinaria, J.A. (2007). Extending ACOR to solve multi-objective problems. In: 2007 UK Workshop on Computational Intelligence (UKCI 2007). Aberdeen University, United Kingdom. [pdf]
Garcia-Najera, A. and Brizuela, C.A. (2005). PCB assembly: An efficient genetic algorithm for slot assignment and component pick and place sequence problems. In: 2005 IEEE Congress on Evolutionary Computation (IEEE CEC 2005), vol. 2, pp. 1485-1492. IEEE. [pdf]
Garcia-Najera, A. (2010). Multi-objective evolutionary algorithms for vehicle routing problems. PhD, University of Birmingham, United Kingdom. [pdf]
García Nájera, A. (2005). Algoritmos genéticos para problemas de ensamble de tarjetas de circuitos impresos. MSc, Centro de Investigación Científica y Educación Superior de Ensenada, Baja California, México. [pdf]
García Nájera, A. and Rodríguez Basabe, A. (1998). Análisis espectral y sistemas de comunicación. BSc, Universidad Autónoma Metropolitana, Unidad Iztapalapa, México, D.F., México.