Publications

Journal Publications

Related to Activity T1:

 1.     Daniel H. Stolfi, Enrique Alba, “Epigenetic algorithms: A New way of building GAs based on epigenetics”, Information Sciences 424: 250-272, 2018, https://doi.org/10.1016/j.ins.2017.10.005.

2.     Martín Pedemonte, Francisco Luna, Enrique Alba, “A theoretical and empirical study of the trajectories of solutions on the grid of Systolic Genetic Search”, Information Sciences, 445–446: 97-117, 2018, https://doi.org/10.1016/j.ins.2018.02.033.

3.     Toutouh, J.; Arellano, J.; Alba, E. BiPred: A Bilevel Evolutionary Algorithm for Prediction in Smart Mobility. Sensors 2018, 18, 4123.

4.     Dahi, Z.A. & Alba, E.; “The grid-to-neighbourhood relationship in cellular GAs: from design to solving complex problems”, Soft Computing (2019). https://doi.org/10.1007/s00500-019-04125-w

5.     Amr Abdelhafez, Enrique Alba, Gabriel Luque, “Performance analysis of synchronous and asynchronous distributed genetic algorithms on multiprocessors”, Swarm and Evolutionary Computation 49: 147-157, 2019, https://doi.org/10.1016/j.swevo.2019.06.003.

 

Related to Activity T3a:

6.     Javier Arellano-Verdejo, Federico Alonso-Pecina, Enrique Alba & Adolfo Guzmán Arenas (2019) Optimal allocation of public parking spots in a smart city: problem characterisation and first algorithms, Journal of Experimental & Theoretical Artificial Intelligence, 31:4, 575-597, DOI: 10.1080/0952813X.2019.1591522

 

Related to Activity T3a:

7.     Daniel H. Stolfi, Enrique Alba, Green Swarm: Greener routes with bio-inspired techniques, Applied Soft Computing 71: 952-963, 2018, https://doi.org/10.1016/j.asoc.2018.07.032.

8.     J. Toutouh, J. Arellano, and E. Alba (2018). BiPred: A Bilevel Evolutionary Algorithm for Prediction in Smart Mobility. Sensors, 18(12), 4123. doi: 10.3390/s18124123

9.     Cintrano, C., Chicano F., & Alba E. (2019).  Facing robustness as a multi-objective problem: A bi-objective shortest path problem in smart regions. Information Sciences. 503, 255 - 273.

 

Related to Activity T6a:

10.   E. Segredo, G. Luque, C. Segura and E. Alba, "Optimising Real-World Traffic Cycle Programs by Using Evolutionary Computation," in IEEE Access, vol. 7, pp. 43915-43932, 2019. doi: 10.1109/ACCESS.2019.2908562

11.  Javier Ferrer, Manuel López-Ibáñez, Enrique Alba, “Reliable simulation-optimization of traffic lights in a real-world city”, Applied Soft Computing 78: 697-711, 2019, https://doi.org/10.1016/j.asoc.2019.03.016.

12.  Andrés Camero, Javier Arellano-Verdejo, Enrique Alba, “Road map partitioning for routing by using a micro steady state evolutionary algorithm”, Engineering Applications of Artificial Intelligence 71: 155-165, 2018, https://doi.org/10.1016/j.engappai.2018.02.016.

13.  Daniel H. Stolfi, Enrique Alba, “Generating realistic urban traffic flows with evolutionary techniques”, Engineering Applications of Artificial Intelligence 75: 36-47, 2018, https://doi.org/10.1016/j.engappai.2018.07.009.

14.  Andrés Camero, Enrique Alba, “Smart City and information technology: A review”, Cities 93: 84-94, 2019, https://doi.org/10.1016/j.cities.2019.04.014.

 

Related to Activity T6b:

 15.  Zakaria Abdelmoiz Dahi, Enrique Alba, Amer Draa, “A stop-and-start adaptive cellular genetic algorithm for mobility management of GSM-LTE cellular network users”, Expert Systems with Applications 106: 290-304, 2018, https://doi.org/10.1016/j.eswa.2018.02.041.

16.  Jamal Toutouh, Enrique Alba, “A swarm algorithm for collaborative traffic in vehicular networks”, Vehicular Communications 12: 127-137, 2018, https://doi.org/10.1016/j.vehcom.2018.04.003.

17. J. Á. Morell, A. Camero and E. Alba, "JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training," in IEEE Access, vol. 7, pp. 158671-158684, 2019, doi: 10.1109/ACCESS.2019.2950287.

Related to Activity T7a:

 18.  J. Toutouh, D. G. Rossit, and S. Nesmachnow (2019). Methods for multiobjective location of garbage accumulation points in smart cities. Annals of Mathematics and Artificial Intelligence (In Pres) Soft computing. doi: 0.1007/s10472-019-09647-5.

19.  D. G. Rossit, S. Nesmachnow, and J. Toutouh (2019). A bi-objective integer programming model for locating garbage accumulation points: a case study. Revista de Ingeniería (In Pres) doi: 10.17533/udea.redin.20190509.

 

Related to Activity T7b:

 20.  Abdelhafez, A., Alba, E. & Luque, G.; “A component-based study of energy consumption for sequential and parallel genetic algorithms”, J Supercomput (2019). https://doi.org/10.1007/s11227-019-02843-4

21.  Camero, A.; Luque, G.; Bravo, Y.; Alba, E. “Customer Segmentation Based on the Electricity Demand Signature: The Andalusian Case”. Energies 2018, 11, 1788.

 

Conference publications

Name of the congress, type of communication (invited, oral, poster), authors

 

Related to Activity T1:

 1.     Jamal Toutouh, Erik Hemberg, and Una-May O’Reilly. 2019. Spatial Evolutionary Generative Adversarial Networks. In Genetic and Evolutionary Computation Conference (GECCO ’19), July 13–17, 2019, Prague, Czech Republic. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3321707.3321860

2.     Reduction of the Size of Datasets by Using Evolutionary Feature Selection: The Case of Noise in a Modern City. Javier Luque, Jamal Toutouh, Enrique Alba. CAEPIA 2018: 230-239

3. Camero, A., Toutouh, J., and Alba, E. Comparing Deep Recurrent Networks Based on the MAE Random Sampling, a First Approach. To appear in Conference of the Spanish Association for Artificial Intelligence, CAEPIA, 2018.
 

4.     Chicano, F., Ochoa G., Whitley D., & ós R. (2018).  Enhancing partition crossover with articulation points analysis. (Aguirre, H., Ed.).the Genetic and Evolutionary Computation Conference Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '18.

5.     Chicano, F., Ochoa G., Whitley D., & Tinos R. (2019).  Quasi-Optimal Recombination Operator. (Liefooghe, A., & Paquete L., Ed.).Lecture Notes in Computer Science. 11452, 131 - 146.

6.     Ochoa, G., & Chicano F. (2019).  Local optima network analysis for MAX-SAT. GECCO 2019.

 

Related to Activity T3a:

7.     Evolutionary Deep Learning for Car Park Occupancy Prediction in Smart Cities. Andrés Camero, Jamal Toutouh, Daniel H. Stolfi, Enrique Alba. LION 2018: 386-401

 

Related to Activity T3b:

8.     An Intelligent Advisor for City Traffic Policies. Daniel H. Stolfi, Christian Cintrano, Francisco Chicano, Enrique Alba. CAEPIA 2018: 383-393

9.     Natural evolution tells us how to best make goods delivery: use vans. Daniel H. Stolfi, Christian Cintrano, Francisco Chicano, Enrique Alba. GECCO (Companion) 2018: 308-309

 

Related to Activity T5b:

10.     Studying Solutions of the p-Median Problem for the Location of Public Bike Stations. Christian Cintrano, Francisco Chicano, Thomas Stützle, Enrique Alba. CAEPIA 2018: 198-208

 

Related to Activity T6b:

11.  José Á. Morell, Enrique Alba: Running Genetic Algorithms in the Edge: A First Analysis. CAEPIA 2018: 251-261

 

Related to Activity T7a:

12.  Javier Ferrer y Enrique Alba. BIN-CT: Sistema Inteligente para la gestión de la recogida de residuos urbanos. International Greencities Congress, p.117-128, 2018

13.  Andrés Camero, Jamal Toutouh, Javier Ferrer, Enrique Alba. Waste generation prediction in smart cities through deep neuroevolution. Ibero-American Congress on Information Management and Big Data. ICSC-CITIES 2018: Smart Cities pp 192-204

14.  Javier Ferrer y Enrique Alba, BIN-CT: Sistema Inteligente para la gestión de la recogida de residuos urbanos [Poster]

15. Camero A, Toutouh J, Ferrer J, Alba E. Waste generation prediction under uncertainty in smart cities through deep neuroevolution. Revista Facultad de Ingeniería Universidad de Antioquia. 2019 Dec(93):128-38.

 

Other publications

1. Camero, A., Toutouh, J., and Alba, E. Low-cost recurrent neural network expected performance evaluation. arXiv preprint arXiv:1805.07159 (may 2018)

2. Camero, A., Toutouh, J., and Alba, E. DLOPT: Deep Learning Optimization Library. arXiv preprint arXiv:1807.03523 (july 2018)


3. Camero A, Toutouh J, Alba E. A specialized evolutionary strategy using mean absolute error random sampling to design recurrent neural networks. arXiv preprint arXiv:1909.02425. 2019 Sep 4.

4. Camero A, Wang H, Alba E, Bäck T. Bayesian Neural Architecture Search using A Training-Free Performance Metric. arXiv preprint arXiv:2001.10726. 2020 Jan 29.