Dr. Diego Alberto Oliva Navarro


  • Doctor of Engineering, Informatics, Complutense University of Madrid, Madrid, Spain. 2001 - 2015.
  • Master of Science, Electronics engineering and computer science, University of Guadalajara, Jalisco, Mexico. 2008 - 2010.
  • Bachelor of Engineering, Electronics engineering and computer sciences, Industrial Technical Education Center (CETI), Guadalajara, Mexico. 2003 - 2007.



  • Anter, A. M., Oliva, D., Thakare, A., & Zhang, Z. (2021). AFCM-LSMA: New intelligent model based on Lévy slime mould algorithm and adaptive fuzzy C-means for identification of COVID-19 infection from chest X-ray images. Advanced Engineering Informatics, 49, 101317. https://doi.org/10.1016/j.aei.2021.101317
  • Abd Elaziz, M., Mohammadi, D., Oliva, D., & Salimifard, K. (2021). Quantum marine predators algorithm for addressing multilevel image segmentation. Applied Soft Computing, 110, 107598. https://doi.org/10.1016/j.asoc.2021.107598
  • Juan, A. A., Keenan, P., Martí, R., McGarraghy, S., Panadero, J., Carroll, P., & Oliva, D. (2021). A review of the role of heuristics in stochastic optimisation: from metaheuristics to learnheuristics. Annals of Operations Research. Published. https://doi.org/10.1007/s10479-021-04142-9
  • Agrawal, P., Ganesh, T., Oliva, D., & Mohamed, A. W. (2021). S-shaped and V-shaped gaining-sharing knowledge-based algorithm for feature selection. Applied Intelligence. Published. https://doi.org/10.1007/s10489-021-02233-5
  • Abd Elaziz, M., Elsheikh, A. H., Oliva, D., Abualigah, L., Lu, S., & Ewees, A. A. (2021). Advanced Metaheuristic Techniques for Mechanical Design Problems: Review. Archives of Computational Methods in Engineering. Published. https://doi.org/10.1007/s11831-021-09589-4
  • Akbarpour, N., Salehi-Amiri, A., Hajiaghaei-Keshteli, M., & Oliva, D. (2021). An innovative waste management system in a smart city under stochastic optimization using vehicle routing problem. Soft Computing, 25(8), 6707–6727. https://doi.org/10.1007/s00500-021-05669-6
  • Ramos-Soto, O., Rodríguez-Esparza, E., Balderas-Mata, S. E., Oliva, D., Hassanien, A. E., Meleppat, R. K., & Zawadzki, R. J. (2021). An efficient retinal blood vessel segmentation in eye fundus images by using optimized top-hat and homomorphic filtering. Computer Methods and Programs in Biomedicine, 201, 105949. https://doi.org/10.1016/j.cmpb.2021.105949
  • Houssein, E. H., Helmy, B. E. D., Oliva, D., Elngar, A. A., & Shaban, H. (2021). A novel Black Widow Optimization algorithm for multilevel thresholding image segmentation. Expert Systems with Applications, 167, 114159. https://doi.org/10.1016/j.eswa.2020.114159
  • Zhao, D., Liu, L., Yu, F., Heidari, A. A., Wang, M., Oliva, D., Muhammad, K., & Chen, H. (2021). Ant colony optimization with horizontal and vertical crossover search: Fundamental visions for multi-threshold image segmentation. Expert Systems with Applications, 167, 114122. https://doi.org/10.1016/j.eswa.2020.114122
  • Scoczynski, M., Delgado, M., Lüders, R., Oliva, D., Wagner, M., Sung, I., & El Yafrani, M. (2021). Saving computational budget in Bayesian network-based evolutionary algorithms. Natural Computing. Published. https://doi.org/10.1007/s11047-021-09849-z
  • Yousri, D., Abd Elaziz, M., Abualigah, L., Oliva, D., Al-qaness, M. A., & Ewees, A. A. (2021). COVID-19 X-ray images classification based on enhanced fractional-order cuckoo search optimizer using heavy-tailed distributions. Applied Soft Computing, 101, 107052. https://doi.org/10.1016/j.asoc.2020.107052
  • Ewees, A. A., Abd Elaziz, M., & Oliva, D. (2021). A new multi-objective optimization algorithm combined with opposition-based learning. Expert Systems with Applications, 165, 113844. https://doi.org/10.1016/j.eswa.2020.113844
  • Aranguren, I., Valdivia, A., Morales-Castañeda, B., Oliva, D., Abd Elaziz, M., & Perez-Cisneros, M. (2021). Improving the segmentation of magnetic resonance brain images using the LSHADE optimization algorithm. Biomedical Signal Processing and Control, 64, 102259. https://doi.org/10.1016/j.bspc.2020.102259
  • Ismaeel, A. A. K., Houssein, E. H., Oliva, D., & Said, M. (2021). Gradient-Based Optimizer for Parameter Extraction in Photovoltaic Models. IEEE Access, 9, 13403–13416. https://doi.org/10.1109/access.2021.3052153
  • Dhiman, G., Oliva, D., Kaur, A., Singh, K. K., Vimal, S., Sharma, A., & Cengiz, K. (2021). BEPO: A novel binary emperor penguin optimizer for automatic feature selection. Knowledge-Based Systems, 211, 106560. https://doi.org/10.1016/j.knosys.2020.106560
  • Micev, M., Ćalasan, M., & Oliva, D. (2021). Design and robustness analysis of an Automatic Voltage Regulator system controller by using Equilibrium Optimizer algorithm. Computers & Electrical Engineering, 89, 106930. https://doi.org/10.1016/j.compeleceng.2020.106930
  • del Río, A. H., Aranguren, I., Oliva, D., Elaziz, M. A., & Cuevas, E. (2020). Efficient image segmentation through 2D histograms and an improved owl search algorithm. International Journal of Machine Learning and Cybernetics, 12(1), 131–150. https://doi.org/10.1007/s13042-020-01161-z
  • Oliva, D., Copado, P., Hinojosa, S., Panadero, J., Riera, D., & Juan, A. A. (2020). Fuzzy Simheuristics: Solving Optimization Problems under Stochastic and Uncertainty Scenarios. Mathematics, 8(12), 2240. https://doi.org/10.3390/math8122240
  • Ibrahim, R. A., Abd Elaziz, M., Oliva, D., & Lu, S. (2020). An improved runner-root algorithm for solving feature selection problems based on rough sets and neighborhood rough sets. Applied Soft Computing, 97, 105517. https://doi.org/10.1016/j.asoc.2019.105517
  • Yousri, D., Abd Elaziz, M., Oliva, D., Abualigah, L., Al-qaness, M. A., & Ewees, A. A. (2020). Reliable applied objective for identifying simple and detailed photovoltaic models using modern metaheuristics: Comparative study. Energy Conversion and Management, 223, 113279. https://doi.org/10.1016/j.enconman.2020.113279
  • Hussien, A. G., Oliva, D., Houssein, E. H., Juan, A. A., & Yu, X. (2020). Binary Whale Optimization Algorithm for Dimensionality Reduction. Mathematics, 8(10), 1821. https://doi.org/10.3390/math8101821
  • Rodríguez-Esparza, E., Zanella-Calzada, L. A., Oliva, D., Heidari, A. A., Zaldivar, D., Pérez-Cisneros, M., & Foong, L. K. (2020). An efficient Harris hawks-inspired image segmentation method. Expert Systems with Applications, 155, 113428. https://doi.org/10.1016/j.eswa.2020.113428
  • Houssein, E. H., Hosney, M. E., Elhoseny, M., Oliva, D., Mohamed, W. M., & Hassaballah, M. (2020). Hybrid Harris hawks optimization with cuckoo search for drug design and discovery in chemoinformatics. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-71502-z
  • Ortega-Sánchez, N., Oliva, D., Cuevas, E., Pérez-Cisneros, M., & Juan, A. A. (2020). An Evolutionary Approach to Improve the Halftoning Process. Mathematics, 8(9), 1636. https://doi.org/10.3390/math8091636
  • López-López, I., Sosa-Gómez, G., Segura, C., Oliva, D., & Rojas, O. (2020). Metaheuristics in the Optimization of Cryptographic Boolean Functions. Entropy, 22(9), 1052. https://doi.org/10.3390/e22091052
  • Oliva, D., & Elaziz, M. A. (2020). An improved brainstorm optimization using chaotic opposite-based learning with disruption operator for global optimization and feature selection. Soft Computing, 24(18), 14051–14072. https://doi.org/10.1007/s00500-020-04781-3
  • Bala, A., Ismail, I., Ibrahim, R., Sait, S. M., & Oliva, D. (2020). An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines. IEEE Access, 8, 159773–159789. https://doi.org/10.1109/access.2020.3020356
  • Micev, M., Ćalasan, M., & Oliva, D. (2020). Fractional Order PID Controller Design for an AVR System Using Chaotic Yellow Saddle Goatfish Algorithm. Mathematics, 8(7), 1182. https://doi.org/10.3390/math8071182
  • Hernandez, G. R., Navarro, M. A., Ortega-Sanchez, N., Oliva, D., & Perez-Cisneros, M. (2020). Failure Detection on Electronic Systems Using Thermal Images and Metaheuristic Algorithms. IEEE Latin America Transactions, 18(08), 1371–1380. https://doi.org/10.1109/tla.2020.9111672
  • Elaziz, M. A., Ewees, A. A., & Oliva, D. (2020). Hyper-heuristic method for multilevel thresholding image segmentation. Expert Systems with Applications, 146, 113201. https://doi.org/10.1016/j.eswa.2020.113201
  • Abbassi, A., Abbassi, R., Heidari, A. A., Oliva, D., Chen, H., Habib, A., Jemli, M., & Wang, M. (2020). Parameters identification of photovoltaic cell models using enhanced exploratory salp chains-based approach. Energy, 198, 117333. https://doi.org/10.1016/j.energy.2020.117333
  • Oliva, D., Martins, M. S., Osuna-Enciso, V., & de Morais, E. F. (2020). Combining information from thresholding techniques through an evolutionary Bayesian network algorithm. Applied Soft Computing, 90, 106147. https://doi.org/10.1016/j.asoc.2020.106147
  • Rizk-Allah, R. M., Hassanien, A. E., & Oliva, D. (2020). An enhanced sitting–sizing scheme for shunt capacitors in radial distribution systems using improved atom search optimization. Neural Computing and Applications, 32(17), 13971–13999. https://doi.org/10.1007/s00521-020-04799-6
  • Abd Elaziz, M., Sarkar, U., Nag, S., Hinojosa, S., & Oliva, D. (2020). Improving image thresholding by the type II fuzzy entropy and a hybrid optimization algorithm. Soft Computing, 24(19), 14885–14905. https://doi.org/10.1007/s00500-020-04842-7
  • Naji Alwerfali, H. S., A. A. Al-qaness, M., Abd Elaziz, M., Ewees, A. A., Oliva, D., & Lu, S. (2020). Multi-Level Image Thresholding Based on Modified Spherical Search Optimizer and Fuzzy Entropy. Entropy, 22(3), 328. https://doi.org/10.3390/e22030328
  • Ahmad, M., Shabbir, S., Oliva, D., Mazzara, M., & Distefano, S. (2020). Spatial-prior generalized fuzziness extreme learning machine autoencoder-based active learning for hyperspectral image classification. Optik, 206, 163712. https://doi.org/10.1016/j.ijleo.2019.163712
  • editors: Erik Cuevas, G., Oliva, D., & Osuna, V. (2020). Special issue: Bio-inspired algorithms and Bio-systems. Mathematical Biosciences and Engineering, 17(3), 2400–2401. https://doi.org/10.3934/mbe.2020129
  • Houssein, E. H., Hosney, M. E., Oliva, D., Mohamed, W. M., & Hassaballah, M. (2020). A novel hybrid Harris hawks optimization and support vector machines for drug design and discovery. Computers & Chemical Engineering, 133, 106656. https://doi.org/10.1016/j.compchemeng.2019.106656
  • Elhoseny, M., Oliva, D., Osuna-Enciso, V., Hassanien, A. E., & Gunasekaran, M. (2020). Parameter identification of two dimensional digital filters using electro-magnetism optimization. Multimedia Tools and Applications, 79(7–8), 5005–5022. https://doi.org/10.1007/s11042-018-6095-1
  • Boudjemaa, R., Oliva, D., & Ouaar, F. (2020). Fractional Lévy flight bat algorithm for global optimisation. International Journal of Bio-Inspired Computation, 15(2), 100. https://doi.org/10.1504/ijbic.2020.106441
  • Zaldivar, D., Cuevas, E., Maciel, O., Valdivia, A., Chavolla, E., & Oliva, D. (2019). Learning classical and metaheuristic optimization techniques by using an educational platform based on LEGO robots. The International Journal of Electrical Engineering & Education, 58(2), 286–305. https://doi.org/10.1177/0020720918822738
  • Yousri, D., Elaziz, M. A., Merchaoui, M., Rana, K., Babu, T. S., Oliva, D., Ram, P., Rajasekar, N., Alama, D., Eteiba, M., Kler, D., Goswami, Y., & Kumar, V. (2019). Reply on “Reply to comment on Important notes on parameter estimation of solar photovoltaic cell”, by Gnetchejo et al. [Energy Conversion and Management, https://doi.org/10.1016/ j.enconman.2019.111870]. Energy Conversion and Management, 201, 112234. https://doi.org/10.1016/j.enconman.2019.112234
  • Oliva, D., Nag, S., Elaziz, M. A., Sarkar, U., & Hinojosa, S. (2019). Multilevel thresholding by fuzzy type II sets using evolutionary algorithms. Swarm and Evolutionary Computation, 51, 100591. https://doi.org/10.1016/j.swevo.2019.100591
  • Ibrahim, R. A., Elaziz, M. A., Oliva, D., Cuevas, E., & Lu, S. (2019). An opposition-based social spider optimization for feature selection. Soft Computing, 23(24), 13547–13567. https://doi.org/10.1007/s00500-019-03891-x
  • Maciel, O., Valdivia, A., Oliva, D., Cuevas, E., Zaldívar, D., & Pérez-Cisneros, M. (2019). A novel hybrid metaheuristic optimization method: hypercube natural aggregation algorithm. Soft Computing, 24(12), 8823–8856. https://doi.org/10.1007/s00500-019-04416-2
  • Oliva, D., Elaziz, M. A., Elsheikh, A. H., & Ewees, A. A. (2019). A review on meta-heuristics methods for estimating parameters of solar cells. Journal of Power Sources, 435, 126683. https://doi.org/10.1016/j.jpowsour.2019.05.089
  • Ibrahim, R. A., Ewees, A. A., Oliva, D., Abd Elaziz, M., & Lu, S. (2019). Improved salp swarm algorithm based on particle swarm optimization for feature selection. Journal of Ambient Intelligence and Humanized Computing, 10(8), 3155–3169. https://doi.org/10.1007/s12652-018-1031-9
  • Elaziz, M. A., Oliva, D., Ewees, A. A., & Xiong, S. (2019). Multi-level thresholding-based grey scale image segmentation using multi-objective multi-verse optimizer. Expert Systems with Applications, 125, 112–129. https://doi.org/10.1016/j.eswa.2019.01.047
  • Anter, A. M., Hassenian, A. E., & Oliva, D. (2019). An improved fast fuzzy c-means using crow search optimization algorithm for crop identification in agricultural. Expert Systems with Applications, 118, 340–354. https://doi.org/10.1016/j.eswa.2018.10.009
  • Avalos, O., Cuevas Jimenez, E. V., Valdivia-González, A., Gálvez, J., Hinojosa, S., Zaldívar, D., & Oliva, D. (2019). A Comparative Study of Evolutionary Computation Techniques for Solar Cells Parameter Estimation. Computación y Sistemas, 23(1). https://doi.org/10.13053/cys-23-1-2881
  • Hinojosa, S., Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Pérez-Cisneros, M. (2019). Reducing overlapped pixels: a multi-objective color thresholding approach. Soft Computing, 24(9), 6787–6807. https://doi.org/10.1007/s00500-019-04315-6
  • Jia, H., Lang, C., Oliva, D., Song, W., & Peng, X. (2019). Dynamic Harris Hawks Optimization with Mutation Mechanism for Satellite Image Segmentation. Remote Sensing, 11(12), 1421. https://doi.org/10.3390/rs11121421
  • Jia, H., Lang, C., Oliva, D., Song, W., & Peng, X. (2019b). Hybrid Grasshopper Optimization Algorithm and Differential Evolution for Multilevel Satellite Image Segmentation. Remote Sensing, 11(9), 1134. https://doi.org/10.3390/rs11091134
  • Jia, Peng, Song, Oliva, Lang, & Yao. (2019). Masi Entropy for Satellite Color Image Segmentation Using Tournament-Based Lévy Multiverse Optimization Algorithm. Remote Sensing, 11(8), 942. https://doi.org/10.3390/rs11080942
  • Oliva, D., Hinojosa, S., Osuna-Enciso, V., Cuevas, E., Pérez-Cisneros, M., & Sanchez-Ante, G. (2019). Image segmentation by minimum cross entropy using evolutionary methods. Soft Computing, 23(2), 431–450. https://doi.org/10.1007/s00500-017-2794-1
  • Hinojosa, S., Dhal, K. G., Elaziz, M. A., Oliva, D., & Cuevas, E. (2018). Entropy-based imagery segmentation for breast histology using the stochastic fractal search. Neurocomputing, 321, 201-215.
  • Hinojosa, S., Avalos, O., Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Gálvez, J. (2018). Unassisted thresholding based on multi-objective evolutionary algorithms. Knowledge-Based Systems, 159, 221-232.
  • Oliva, D., Hinojosa, S., Elaziz, M. A., & Ortega-Sánchez, N. (2018). Context based image segmentation using antlion optimization and sine cosine algorithm. Multimedia Tools and Applications, 77(19), 25761-25797.
  • Elaziz, M. A., & Oliva, D. (2018). Parameter estimation of solar cells diode models by an improved opposition-based whale optimization algorithm. Energy conversion and management, 171, 1843-1859.
  • Gálvez, J., Cuevas, E., Avalos, O., Oliva, D., & Hinojosa, S. (2018). Electromagnetism-like mechanism with collective animal behavior for multimodal optimization. Applied Intelligence, 48(9), 2580-2612.
  • Díaz-Cortés, M. A., Ortega-Sánchez, N., Hinojosa, S., Oliva, D., Cuevas, E., Rojas, R., & Demin, A. (2018). A multi-level thresholding method for breast thermograms analysis using Dragonfly algorithm. Infrared Physics & Technology, 93, 346-361.
  • Issa, M., Hassanien, A. E., Oliva, D., Helmi, A., Ziedan, I., & Alzohairy, A. (2018). ASCA-PSO: Adaptive sine cosine optimization algorithm integrated with particle swarm for pairwise local sequence alignment. Expert Systems with Applications, 99, 56-70.
  • Elhoseny, M., Oliva, D., Osuna-Enciso, V., Hassanien, A. E., & Gunasekaran, M. (2018). Parameter identification of two dimensional digital filters using electro-magnetism optimization. Multimedia Tools and Applications, 1-18.
  • Hinojosa, S., Oliva, D., Cuevas, E., Pajares, G., Avalos, O., & Gálvez, J. (2018). Improving multi-criterion optimization with chaos: a novel Multi-Objective Chaotic Crow Search Algorithm. Neural Computing and Applications, 29(8), 319-335.
  • Osuna-Enciso, V., Espinoza-Haro, J. I., Oliva, D., & Hernández-Ahuactzi, I. F. (2018). Offshore Wind Farm Layout Optimization via Differential Evolution. Computación y Sistemas, 22(3), 929-941.
  • Друки, А. А., Спицын, В. Г., Болотова, Ю. А., Олива, Д., & Гельгинберг, А. М. Разработка алгоритма отслеживания лица человека на основе применения оптического потока.
  • Elaziz, M. A., Oliva, D., & Xiong, S. (2017). An improved opposition-based sine cosine algorithm for global optimization. Expert Systems with Applications, 90, 484-500.
  • Elaziz, M. A., Hemdan, A. M., Hassanien, A., Oliva, D., & Xiong, S. (2017). Analysis of bioactive amino acids from fish hydrolysates with a new bioinformatic intelligent system approach. Scientific reports, 7(1), 1-9.
  • Oliva, D., El Aziz, M. A., & Hassanien, A. E. (2017). Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm. Applied Energy, 200, 141-154.
  • Oliva, D., Hinojosa, S., Cuevas, E., Pajares, G., Avalos, O., & Gálvez, J. (2017). Cross entropy based thresholding for magnetic resonance brain images using Crow Search Algorithm. Expert Systems with Applications, 79, 164-180.
  • Oliva, D., Ewees, A. A., Aziz, M. A. E., Hassanien, A. E., & Peréz-Cisneros, M. (2017). A chaotic improved artificial bee colony for parameter estimation of photovoltaic cells. Energies, 10(7), 865.
  • Osuna-Enciso, V., Cuevas, E., Oliva, D., Sossa, H., & Cisneros, M. A. P. (2016). A bio-inspired evolutionary algorithm: allostatic optimisation. IJBIC, 8(3), 154-169.
  • Osuna-Enciso, V., Zúñiga, V., Oliva, D., Cuevas, E., & Sossa, H. (2016). Image segmentation using an evolutionary method based on Allostatic mechanisms. In Image feature detectors and descriptors (pp. 255-279). Springer, Cham.
  • Osuna-Enciso, V., Cuevas, E., Oliva, D., Zúñiga, V., Pérez-Cisneros, M., & Zaldívar, D. (2016). A multiobjective approach to homography estimation. Computational intelligence and neuroscience, 2016.
  • Oliva, D., Osuna-Enciso, V., Cuevas, E., Pajares, G., Pérez-Cisneros, M., & Zaldívar, D. (2015). Improving segmentation velocity using an evolutionary method. Expert Systems with Applications, 42(14), 5874-5886.
  • Cuevas, E., Osuna-Enciso, V., & Oliva, D. (2015). Circle detection on images based on the Clonal Selection Algorithm (CSA). The Imaging Science Journal, 63(1), 34-44.
  • Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Osuna, V. (2014). A multilevel thresholding algorithm using electromagnetism optimization. Neurocomputing, 139, 357-381.
  • Oliva, D., Cuevas, E., & Pajares, G. (2014). Parameter identification of solar cells using artificial bee colony optimization. Energy, 72, 93-102.
  • Oliva, D., Cuevas, E., Pajares, G., & Zaldivar, D. (2014). Template matching using an improved electromagnetism-like algorithm. Applied intelligence, 41(3), 791-807.
  • Oliva, D., Cuevas, E., Pajares, G., Zaldivar, D., & Perez-Cisneros, M. (2013). Multilevel thresholding segmentation based on harmony search optimization. Journal of Applied Mathematics, 2013.
  • Cuevas, E., Oliva, D., Zaldivar, D., Pérez, M., & Rojas, R. (2013). Circle detection algorithm based on electromagnetism-like optimization. In Handbook of Optimization (pp. 907-934). Springer, Berlin, Heidelberg.
  • Cuevas, E., Oliva, D., Díaz, M., Zaldivar, D., Pérez-Cisneros, M., & Pajares, G. (2013). White blood cell segmentation by circle detection using electromagnetism-like optimization. Computational and mathematical methods in medicine, 2013.
  • Cuevas, E., ZaldíVar, D., Pérez-Cisneros, M., & Oliva, D. (2013). Block-matching algorithm based on differential evolution for motion estimation. Engineering Applications of Artificial Intelligence, 26(1), 488-498.
  • Cuevas, E., Oliva, D., Zaldivar, D., Perez, M., & Pajares, G. (2014). Opposition Based ElectromagnetismLike for Global Optimization. arXiv preprint arXiv:1405.5172.
  • Cuevas, E., Oliva, D., Zaldivar, D., Pérez-Cisneros, M., & Sossa, H. (2012). Circle detection using electro-magnetism optimization. Information Sciences, 182(1), 40-55.



  • Oliva, D., & Hinojosa, S. (2020). Applications of Hybrid Metaheuristic Algorithms for Image Processing (Studies in Computational Intelligence Book 890) (English Edition) (1st ed. 2020 ed.). Springer.
  • Hassanien, A., Azar, A. T., Gaber, T., Oliva, D., & Tolba, F. M. (2020). Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020) (Advances in Intelligent Systems and Computing Book 1153) (English Edition) (1st ed. 2020 ed.). Springer.
  • Oliva, D., Elaziz, A. M., & Hinojosa, S. (2019). Metaheuristic Algorithms for Image Segmentation: Theory and Applications (Studies in Computational Intelligence Book 825) (English Edition) (1st ed. 2019 ed.). Springer.
  • Oliva, D., & Cuevas, E. (2017). Advances and applications of optimised algorithms in image processing. Springer International Publishing.
  • Cuevas, E., Osuna, V., & Oliva, D. (2017). Evolutionary computation techniques: a comparative perspective (Vol. 686). Berlin: Springer.
  • Cuevas, E., Cortés, M. A. D., & Navarro, D. A. O. (2016). Advances of evolutionary computation: methods and operators. Springer International Publishing.
  • Ochoa, A., Contreras-Masse, R., Mejia, J. M., & Oliva, D. (2021). Preservation of Cultural Heritage in an Ethnic Minority Using Internet of Things and Smart Karaoke. Handbook of Research on Natural Language Processing and Smart Service Systems, 180–195. https://doi.org/10.4018/978-1-7998-4730-4.ch008
  • Elhoseny, M., Nabil, A., Hassanien, A. E., & Oliva, D. (2018). Hybrid rough neural network model for signature recognition. In Advances in Soft Computing and Machine Learning in Image Processing (pp. 295-318). Springer, Cham.
  • Oliva, D., Cuevas, E., Pajares, G., Zaldívar, D., Pérez-Cisneros, M., & Osuna-Enciso, V. (2016). Harmony Search Optimization for Multilevel Thresholding in Digital Images. In Evolutionary Computation (pp. 137-186). Apple Academic Press.
  • Houssein, E. H., Hosney, M. E., & Oliva, D. (2021). A hybrid seagull optimization algorithm for chemical descriptors classification. 2021 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC). Published. https://doi.org/10.1109/miucc52538.2021.9447659
  • Mousavirad, S. J., Schaefer, G., Korovin, I., & Oliva, D. (2021). RDE-OP: A Region-Based Differential Evolution Algorithm Incorporation Opposition-Based Learning for Optimising the Learning Process of Multi-layer Neural Networks. Applications of Evolutionary Computation, 407–420. https://doi.org/10.1007/978-3-030-72699-7_26
  • Oliva, D., Rodriguez-Esparza, E., Martins, M. S. R., Abd Elaziz, M., Hinojosa, S., Ewees, A. A., & Lu, S. (2020). Balancing the Influence of Evolutionary Operators for Global optimization. 2020 IEEE Congress on Evolutionary Computation (CEC). Published. https://doi.org/10.1109/cec48606.2020.9185766
  • Elaziz, M. A., Ewees, A. A., Yousri, D., Oliva, D., Lu, S., & Cuevas, E. (2020). A Competitive Swarm Algorithm for Image Segmentation Guided by Opposite Fuzzy Entropy. 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Published. https://doi.org/10.1109/fuzz48607.2020.9177624
  • El-dosuky, M. A., Oliva, D., & Hassanien, A. E. (2020). An Artificial Intelligence System for Apple Fruit Disease Classification Based on Support Vector Machine and Cockroach Swarm Optimization. Advances in Intelligent Systems and Computing, 137–147. https://doi.org/10.1007/978-3-030-44289-7_14
  • Abd El-aziz, A. A., Darwish, A., Oliva, D., & Hassanien, A. E. (2020). Machine Learning for Apple Fruit Diseases Classification System. Advances in Intelligent Systems and Computing, 16–25. https://doi.org/10.1007/978-3-030-44289-7_2
  • Garcia, H., Ochoa-Zezzatti, A., Martínez-Retamoza, A., Ochoa, G., Aguilar, L., Oliva, D., & Mejía, J. (2020). Use of Deep Learning for Bird Detection to Reduction of Collateral Damage in Fruit Fields. Advances in Intelligent Systems and Computing, 381–392. https://doi.org/10.1007/978-3-030-44289-7_36
  • Rodríguez-Esparza, E., Zanella-Calzada, L. A., Oliva, D., & Pérez-Cisneros, M. (2020). Automatic detection and classification of abnormal tissues on digital mammograms based on a bag-of-visual-words approach. Medical Imaging 2020: Computer-Aided Diagnosis. Published. https://doi.org/10.1117/12.2549899
  • Premebida, S., Pechebovicz, D., Camargo, T., Nazario, H., Soa, V., Baroncini, V., de Morais, E., Siqueira, H., Oliva, D., & Martins, M. (2020). Sunspot behavior forecast using neural networks approaches. 2020 IEEE International Conference on Industrial Technology (ICIT). Published. https://doi.org/10.1109/icit45562.2020.9067206
  • Elaziz, M. A., Lu, S., Oliva, D., & El-Abd, M. (2019). Improved Moth-Flame Optimization Based on Opposition-Based Learning for Feature Selection. 2019 IEEE Symposium Series on Computational Intelligence (SSCI). Published. https://doi.org/10.1109/ssci44817.2019.9002898
  • Oliva, D., Hinojosa, S., Martins, M. S. R., Rodriguez-Esparza, E., Ortega-Sanchez, N., & Perez-Cisneros, M. (2019). Improving the estimation of parameters in induction motors using an evolutionary computation algorithm. 2019 IEEE Latin American Conference on Computational Intelligence (LA-CCI). Published. https://doi.org/10.1109/la-cci47412.2019.9037056
  • Rodriguez-Esparza, E., Zanella-Calzada, L. A., Oliva, D., Hinojosa, S., & Perez-Cisneros, M. (2019b). Multilevel segmentation for automatic detection of malignant masses in digital mammograms based on threshold comparison. 2019 IEEE Latin American Conference on Computational Intelligence (LA-CCI). Published. https://doi.org/10.1109/la-cci47412.2019.9037030
  • El Yafrani, M., Scoczynski, M., Delgado, M., Luders, R., Sung, I., Wagner, M., & Oliva, D. (2019). On Updating Probabilistic Graphical Models in Bayesian Optimisation Algorithm. 2019 8th Brazilian Conference on Intelligent Systems (BRACIS). Published. https://doi.org/10.1109/bracis.2019.00062
  • Oliva, D., & Martins, M. S. R. (2019). A Bayesian based Hyper-Heuristic approach for global optimization. 2019 IEEE Congress on Evolutionary Computation (CEC). Published. https://doi.org/10.1109/cec.2019.8790028
  • Camargo, T. O., Pechebovicz, D., Premebida, S. M., Soares, V. R., Baroncini, V., Siqueira, H., Oliva, D., & Martins, M. (2019). Detecting a predefined solar spot group with a pretrained convolutional neural network. 2019 IEEE Colombian Conference on Applications in Computational Intelligence (ColCACI). Published. https://doi.org/10.1109/colcaci.2019.8781990
  • Ochoa, A., & Oliva, D. (2018, November). Smart traffic management to support people with color blindness in a Smart City. In 2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI) (pp. 1-8). IEEE.
  • Hinojosa, S., Avalos, O., Gálvez, J., Oliva, D., Cuevas, E., & Pérez-Cisneros, M. (2018, November). Remote sensing imagery segmentation based on multi-objective optimization algorithms. In 2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI) (pp. 1-6). IEEE.
  • Contreras, R., Ochoa, A., Cossío, E., García, V., Oliva, D., & Torres, R. (2018, December). Design and Implementation of an IoT-Based Háptical Interface Implemented by Memetic Algorithms to Improve Competitiveness in an Industry 4.0 Model for the Manufacturing Sector. In International Conference on Innovations in Bio-Inspired Computing and Applications (pp. 103-117). Springer, Cham.
  • Camargo, T. O., Premebida, S. M., Pechebovicz, D., Soares, V. R., Martins, M., Baroncini, V., ... & Oliva, D. (2019, June). Solar Spots Classification Using Pre-processing and Deep Learning Image Techniques. In IEEE Colombian Conference on Applications in Computational Intelligence <7(pp. 235-246). Springer, Cham.
  • Hinojosa, S., Oliva, D., Cuevas, E., Pérez-Cisneros, M., & Pájares, G. (2018, May). Real-time video thresholding using evolutionary techniques and cross entropy. In 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS) (pp. 1-8). IEEE.
  • Diego, O., Demin, A., & Demeshko, M. (2018). Edge detection using neural network committee. In Труды Международной конференции по компьютерной графики и зрению" Графикон" (No. 28, pp. 66-69). Федеральное государственное учреждение" Федеральный исследовательский центр Институт прикладной математики им. МВ Келдыша Российской академии наук".
  • Oliva, D., Hinojosa, S., & Demeshko, M. V. (2017, January). Engineering applications of metaheuristics: an introduction. In Journal of Physics: Conference Series (Vol. 803, No. 1, p. 012111). IOP Publishing.
  • Ibrahim, R. A., Oliva, D., Ewees, A. A., & Lu, S. (2017, November). Feature selection based on improved runner-root algorithm using chaotic singer map and opposition-based learning. In International conference on neural information processing (pp. 156-166). Springer, Cham.
  • Elaziz, M. E. A., Ewees, A. A., Oliva, D., Duan, P., & Xiong, S. (2017, November). A hybrid method of sine cosine algorithm and differential evolution for feature selection. In International Conference on Neural Information Processing (pp. 145-155). Springer, Cham.

2020 - 2023

Member (Level 2) of the National Research System of Mexico (SNI - CONACYT).

2017 - 2019

Member (Level 1) of the National Research System of Mexico (SNI - CONACYT).

2015 - 2019

Member of the Mexican Academy of Computer Science.

2017 - 2018

Member of IEEE Society of Computacional Intelligence.

2011 - 2015

Full Ph. D. fellowship, National, National Council of Science and Technology of Mexico.

2011 - 2015

Partial Ph. D. fellowship, Youth Institute of Jalisco, Mexico.

2010 - 2010

Full support for a research stay in Berlin, National Council of Science and Technology of Mexico.

2008 - 2015

Full Master´s degree fellowship, National Council of Science and Technology of Mexico.