@Article{Stolfi2024,
   author   = {Daniel H. Stolfi and Grégoire Danoy},
   journal  = {Engineering Applications of Artificial Intelligence},
   title    = {Evolutionary swarm formation: From simulations to real world robots},
   year     = {2024},
   issn     = {0952-1976},
   pages    = {107501},
   volume   = {128},
   doi      = {https://doi.org/10.1016/j.engappai.2023.107501},
   keywords = {Swarm robotics, Evolutionary algorithm, E-Puck2, ARGoS simulator, Robot formation},
   url      = {https://www.sciencedirect.com/science/article/pii/S0952197623016858},
}

@Article{Stolfi2023a,
   author         = {Stolfi, Daniel H. and Danoy, Grégoire},
   journal        = {Applied Sciences},
   title          = {Optimising Robot Swarm Formations by Using Surrogate Models and Simulations},
   year           = {2023},
   issn           = {2076-3417},
   number         = {10},
   volume         = {13},
   abstract       = {Optimising a swarm of many robots can be computationally demanding, especially when accurate simulations are required to evaluate the proposed robot configurations. Consequentially, the size of the instances and swarms must be limited, reducing the number of problems that can be addressed. In this article, we study the viability of using surrogate models based on Gaussian processes and artificial neural networks as predictors of the robots’ behaviour when arranged in formations surrounding a central point of interest. We have trained the surrogate models and tested them in terms of accuracy and execution time on five different case studies comprising three, five, ten, fifteen, and thirty robots. Then, the best performing predictors combined with ARGoS simulations have been used to obtain optimal configurations for the robot swarm by using our proposed hybrid evolutionary algorithm, based on a genetic algorithm and a local search. Finally, the best swarm configurations obtained have been tested on a number of unseen scenarios comprising different initial robot positions to evaluate the robustness and stability of the achieved robot formations. The best performing predictors exhibited speed increases of up to 3604 with respect to the ARGoS simulations. The optimisation algorithm converged in 91% of runs and stable robot formations were achieved in 79% of the unseen testing scenarios.},
   article-number = {5989},
   doi            = {10.3390/app13105989},
   url            = {https://www.mdpi.com/2076-3417/13/10/5989},
}

@Article{Stolfi2023,
   author   = {Daniel H. Stolfi and Grégoire Danoy},
   journal  = {Robotics and Autonomous Systems},
   title    = {Design and analysis of an E-Puck2 robot plug-in for the ARGoS simulator},
   year     = {2023},
   issn     = {0921-8890},
   pages    = {104412},
   volume   = {164},
   doi      = {https://doi.org/10.1016/j.robot.2023.104412},
   keywords = {E-puck2, ARGoS, Computer simulations, Sensors, Swarm robotic},
   url      = {https://www.sciencedirect.com/science/article/pii/S0921889023000519},
}

@Article{Stolfi2022b,
   author         = {Stolfi, Daniel H. and Danoy, Grégoire},
   journal        = {Applied Sciences},
   title          = {An Evolutionary Algorithm to Optimise a Distributed UAV Swarm Formation System},
   year           = {2022},
   issn           = {2076-3417},
   number         = {20},
   volume         = {12},
   article-number = {10218},
   doi            = {10.3390/app122010218},
   url            = {https://www.mdpi.com/2076-3417/12/20/10218},
}

@Article{Stolfi2022a,
   author         = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Grégoire and Bouvry, Pascal},
   journal        = {Drones},
   title          = {SuSy-EnGaD: Surveillance System Enhanced by Games of Drones},
   year           = {2022},
   issn           = {2504-446X},
   number         = {1},
   volume         = {6},
   article-number = {13},
   doi            = {10.3390/drones6010013},
   url            = {https://www.mdpi.com/2504-446X/6/1/13},
}

@article{Stolfi2021c,
   title = {A competitive Predator–Prey approach to enhance surveillance by UAV swarms},
   journal = {Applied Soft Computing},
   volume = {111},
   pages = {107701},
   year = {2021},
   issn = {1568-4946},
   doi = {https://doi.org/10.1016/j.asoc.2021.107701},
   url = {https://www.sciencedirect.com/science/article/pii/S1568494621006220},
   author = {Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry},
   keywords = {Swarm robotics, Computer simulation, Mobility model, Unmanned aerial vehicle, Competitive coevolutionary genetic algorithm},
}

@article{STOLFI2021107566,
   title = {Yellow Swarm: LED panels to advise optimal alternative tours to drivers in the city of Malaga},
   journal = {Applied Soft Computing},
   volume = {109},
   pages = {107566},
   year = {2021},
   issn = {1568-4946},
   doi = {https://doi.org/10.1016/j.asoc.2021.107566},
   url = {https://www.sciencedirect.com/science/article/pii/S1568494621004877},
   author = {Daniel H. Stolfi and Enrique Alba},
   keywords = {epiGenetic algorithm, Smart mobility, LED panel, Travel time, Greenhouse gas emissions, Fuel consumption}
}

@Article{Stolfi2021a,
   author    = {Daniel H. Stolfi and Matthias R. Brust and Gr{\'{e}}goire Danoy and Pascal Bouvry},
   journal   = {Swarm Intelligence},
   title     = {CONSOLE: intruder detection using a UAV swarm and security rings},
   year      = {2021},
   issn      = {1935-3820},
   number    = {3},
   pages     = {205--235},
   volume    = {15},
   doi       = {10.1007/s11721-021-00193-7},
   publisher = {Springer Science and Business Media {LLC}},
   refid     = {Stolfi2021},
   url       = {https://doi.org/10.1007/s11721-021-00193-7},
}

@Article{Brust2021,
   author    = {Matthias R. Brust and Gr{\'{e}}goire Danoy and Daniel H. Stolfi and Pascal Bouvry},
   journal   = {Discover Internet of Things},
   title     = {Swarm-based counter {UAV} defense system},
   year      = {2021},
   month     = {feb},
   number    = {1},
   volume    = {1},
   doi       = {10.1007/s43926-021-00002-x},
   publisher = {Springer Science and Business Media {LLC}},
}

@article{Stolfi2021,
   author = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Gr{\'{e}}goire and Bouvry, Pascal},
   doi = {10.3389/frobt.2021.616950},
   issn = {2296-9144},
   journal = {Frontiers in Robotics and AI},
   month = {feb},
   title = {{UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance}},
   url = {https://www.frontiersin.org/articles/10.3389/frobt.2021.616950/full},
   volume = {8},
   year = {2021}
}

@Article{s20092566,
   AUTHOR = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Grégoire and Bouvry, Pascal},
   TITLE = {Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques},
   JOURNAL = {Sensors},
   VOLUME = {20},
   YEAR = {2020},
   NUMBER = {9},
   ARTICLE-NUMBER = {2566},
   URL = {https://www.mdpi.com/1424-8220/20/9/2566},
   ISSN = {1424-8220},
   DOI = {10.3390/s20092566}
}

@article{doi:10.1080/10630732.2019.1586223,
   author = {Daniel H. Stolfi and Enrique Alba and Xin Yao},
   title = {Can I Park in the City Center? Predicting Car Park Occupancy Rates in Smart Cities},
   journal = {Journal of Urban Technology},
   volume = {27},
   number = {4},
   pages = {27-41},
   year  = {2020},
   publisher = {Routledge},
   doi = {10.1080/10630732.2019.1586223},
   URL = {https://doi.org/10.1080/10630732.2019.1586223},
   eprint = {https://doi.org/10.1080/10630732.2019.1586223}
}

@article{STOLFI2018952,
   author = {Daniel H. Stolfi and Enrique Alba},
   doi = {10.1016/j.asoc.2018.07.032},
   issn = {1568-4946},
   journal = {Applied Soft Computing},
   keywords = {Evolutionary algorithm; Road traffic; Smart city; Smart mobility; Gas emissions; Wi-Fi connections},
   pages = {952--963},
   title = {{Green Swarm: Greener routes with bio-inspired techniques}},
   url = {http://www.sciencedirect.com/science/article/pii/S1568494618304204},
   volume = {71},
   year = {2018}
}

@article{STOLFI201836,
   title = "Generating realistic urban traffic flows with evolutionary techniques",
   journal = "Engineering Applications of Artificial Intelligence",
   volume = "75",
   pages = "36 - 47",
   year = "2018",
   issn = "0952-1976",
   doi = "https://doi.org/10.1016/j.engappai.2018.07.009",
   url = "http://www.sciencedirect.com/science/article/pii/S0952197618301532",
   author = "Daniel H. Stolfi and Enrique Alba",
   keywords = "Evolutionary algorithm, Traffic simulation, Smart mobility, SUMO, Road traffic optimization, O–D matrix"
}

@article{STOLFI2018250,
   author = "Stolfi, Daniel H. and Alba, Enrique",
   doi = "10.1016/j.ins.2017.10.005",
   issn = "0020-0255",
   journal = "Information Sciences",
   keywords = "Evolutionary algorithm; Epigenetics; MKP; Bio-inspiration",
   number = "Supplement C",
   pages = "250--272",
   title = "{Epigenetic algorithms: A New way of building GAs based on epigenetics}",
   url = "http://www.sciencedirect.com/science/article/pii/S0020025517309921",
   volume = "424",
   year = "2018"
}

@article{STOLFI2014181,
   title = "Red Swarm: Reducing travel times in smart cities by using bio-inspired algorithms",
   journal = "Applied Soft Computing",
   volume = "24",
   pages = "181 - 195",
   year = "2014",
   issn = "1568-4946",
   doi = "https://doi.org/10.1016/j.asoc.2014.07.014",
   url = "http://www.sciencedirect.com/science/article/pii/S1568494614003457",
   author = "Daniel H. Stolfi and Enrique Alba",
   keywords = "Evolutionary algorithm, Road traffic, Smart city, Smart mobility, WiFi connections, Traffic light"
}

@incollection{STOLFI2019361,
   title = "Chapter 14 - Sustainable Road Traffic Using Evolutionary Algorithms",
   editor = "Javier Faulin and Scott E. Grasman and Angel A. Juan and Patrick Hirsch",
   booktitle = "Sustainable Transportation and Smart Logistics",
   publisher = "Elsevier",
   pages = "361 - 380",
   year = "2019",
   isbn = "978-0-12-814242-4",
   doi = "https://doi.org/10.1016/B978-0-12-814242-4.00014-4",
   url = "http://www.sciencedirect.com/science/article/pii/B9780128142424000144",
   author = "Daniel H. Stolfi and Enrique Alba",
   keywords = "Evolutionary algorithm, Intelligent transportation systems, LED panels, Road traffic, Smart mobility, Wi-Fi connections"
}

@InProceedings{Stolfi2023c,
   author    = {Stolfi, Daniel H. and Danoy, Gr\'{e}goire},
   booktitle = {Proceedings of the Companion Conference on Genetic and Evolutionary Computation},
   title     = {Spacecraft Swarm Orbital Formation Optimisation Using Evolutionary Techniques},
   year      = {2023},
   address   = {New York, NY, USA},
   pages     = {771–774},
   publisher = {Association for Computing Machinery},
   series    = {GECCO '23 Companion},
   doi       = {10.1145/3583133.3590651},
   isbn      = {9798400701207},
   keywords  = {evolutionary algorithm, simulated annealing, swarm robotics, formation control, spacecraft constellation, orbital simulation},
   location  = {Lisbon, Portugal},
   numpages  = {4},
   url       = {https://doi.org/10.1145/3583133.3590651},
}

@InProceedings{Stolfi2023b,
   author    = {Stolfi, Daniel H. and Danoy, Gr{\'e}goire},
   booktitle = {Optimization and Learning},
   title     = {Evaluating Surrogate Models for Robot Swarm Simulations},
   year      = {2023},
   address   = {Cham},
   editor    = {Dorronsoro, Bernab{\'e} and Chicano, Francisco and Danoy, Gregoire and Talbi, El-Ghazali},
   pages     = {224--235},
   publisher = {Springer Nature Switzerland},
   abstract  = {Realistic robotic simulations are computationally demanding, especially when considering large swarms of autonomous robots. This makes the optimisation of such systems intractable, thus limiting the instances' and swarms' size. In this article we study the viability of using surrogate models based on Gaussian processes, Artificial Neural Networks, and simplified simulations, as predictors of the robots' behaviour, when performing formations around a central point of interest. We have trained the predictors and tested them in terms of accuracy and execution time. Our findings show that they can be used as an alternative way of calculating fitness values for swarm configurations which can be used in optimisation processes, increasing the number evaluations and reducing execution times and computing cluster budget.},
   isbn      = {978-3-031-34020-8},
}

@inproceedings{10.1145/3512290.3528709,
   author = {Stolfi, Daniel H. and Danoy, Gr\'{e}goire},
   title = {Optimising Autonomous Robot Swarm Parameters for Stable Formation Design},
   year = {2022},
   isbn = {9781450392372},
   publisher = {Association for Computing Machinery},
   address = {New York, NY, USA},
   url = {https://doi.org/10.1145/3512290.3528709},
   doi = {10.1145/3512290.3528709},
   booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference},
   pages = {1281--1289},
   numpages = {9},
   keywords = {e-puck2, evolutionary algorithm, formation control, argos3 simulator, swarm robotics},
   location = {Boston, Massachusetts},
   series = {GECCO '22}
}

@InProceedings{10.1007/978-3-030-88081-1_17,
   author="Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Gr{\'e}goire and Bouvry, Pascal",
   editor="Nguyen, Ngoc Thanh and Iliadis, Lazaros and Maglogiannis, Ilias and Trawi{\'{n}}ski, Bogdan",
   title="Improving Pheromone Communication for UAV Swarm Mobility Management",
   booktitle="Computational Collective Intelligence",
   year="2021",
   publisher="Springer International Publishing",
   address="Cham",
   pages="228--240",
   isbn="978-3-030-88081-1",
   doi={10.1007/978-3-030-88081-1_17}
}

@InProceedings{Stolfi2021d,
   author    = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Gr\'{e}goire and Bouvry, Pascal},
   booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference Companion},
   title     = {Optimising Pheromone Communication in a UAV Swarm},
   year      = {2021},
   address   = {New York, NY, USA},
   pages     = {323–324},
   publisher = {Association for Computing Machinery},
   series    = {GECCO '21},
   doi       = {10.1145/3449726.3459526},
   isbn      = {9781450383516},
   keywords  = {mobility model, surveillance system, unmanned aerial vehicle, swarm robotics, pheromones, evolutionary algorithm},
   location  = {Lille, France},
   numpages  = {2},
   url       = {https://doi.org/10.1145/3449726.3459526},
}

@INPROCEEDINGS{9150444,
   author={D. H. {Stolfi} and M. R. {Brust} and G. {Danoy} and P. {Bouvry}},
   booktitle={2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
   title={Competitive Evolution of a UAV Swarm for Improving Intruder Detection Rates},
   year={2020},
   volume={},
   number={},
   pages={528-535},
   doi={10.1109/IPDPSW50202.2020.00094}
}

@InProceedings{10.1007/978-3-030-41913-4_4,
   author="Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Gr{\'e}goire and Bouvry, Pascal",
   editor="Dorronsoro, Bernab{\'e} and Ruiz, Patricia and de la Torre, Juan Carlos and Urda, Daniel and Talbi, El-Ghazali",
   title="Optimizing the Performance of an Unpredictable UAV Swarm for Intruder Detection",
   booktitle="Optimization and Learning",
   year="2020",
   publisher="Springer International Publishing",
   address="Cham",
   pages="37--48",
   isbn="978-3-030-41913-4",
   doi="10.1007/978-3-030-41913-4_4"
}

@INPROCEEDINGS{9045643,
   author={D. H. {Stolfi} and M. R. {Brust} and G. {Danoy} and P. {Bouvry}},
   booktitle={2020 IEEE 17th Annual Consumer Communications   Networking Conference (CCNC)},
   title={A Cooperative Coevolutionary Approach to Maximise Surveillance Coverage of UAV Swarms},
   year={2020},
   volume={},
   number={},
   pages={1-6},
   doi={10.1109/CCNC46108.2020.9045643}
}

@InProceedings{10.1007/978-3-030-05348-2_32,
   author="Camero, Andr{\'e}s
   and Toutouh, Jamal
   and Stolfi, Daniel H.
   and Alba, Enrique",
   editor="Battiti, Roberto
   and Brunato, Mauro
   and Kotsireas, Ilias
   and Pardalos, Panos M.",
   title="Evolutionary Deep Learning for Car Park Occupancy Prediction in Smart Cities",
   booktitle="Learning and Intelligent Optimization",
   year="2019",
   publisher="Springer International Publishing",
   address="Cham",
   pages="386--401",
   isbn="978-3-030-05348-2"
}

@inproceedings{10.1007/978-3-030-00374-6_36,
   address = "Cham",
   author = "Stolfi, Daniel H. and Cintrano, Christian and Chicano, Francisco and Alba, Enrique",
   booktitle = "Advances in Artificial Intelligence",
   editor = "Herrera, Francisco and Damas, Sergio and Montes, Rosana and Alonso, Sergio and Cordón, Óscar and González, Antonio and Troncoso, Alicia",
   isbn = "978-3-030-00374-6",
   pages = "383-393",
   publisher = "Springer International Publishing",
   title = "An Intelligent Advisor for City Traffic Policies",
   year = "2018"
}

@inproceedings{Stolfi:2018:NET:3205651.3205764,
   acmid = "3205764",
   address = "New York, NY, USA",
   author = "Stolfi, Daniel H. and Cintrano, Christian and Chicano, Francisco and Alba, Enrique",
   booktitle = "{Proceedings of the Genetic and Evolutionary Computation Conference Companion}",
   doi = "10.1145/3205651.3205764",
   isbn = "978-1-4503-5764-7",
   keywords = "application; city policy; evolutionary algorithm; real world; road traffic; smart mobility",
   location = "Kyoto, Japan",
   numpages = "2",
   pages = "308--309",
   publisher = "ACM",
   series = "{GECCO '18}",
   title = "{Natural Evolution Tells Us How to Best Make Goods Delivery: Use Vans}",
   url = "http://doi.acm.org/10.1145/3205651.3205764",
   year = "2018"
}

@InProceedings{ALCARAZ2018SOM,
   author = {Alcaraz, C. and Abdo-S{\'{a}}nchez, E. and Toutouh, J. and Halir, R. and Ruiz, M. and Stolfi, D.H.},
   title = {Some Ingredients to Improve Gamification in Engineering},
   series = {10th International Conference on Education and New Learning Technologies},
   booktitle = {EDULEARN18 Proceedings},
   isbn = {978-84-09-02709-5},
   issn = {2340-1117},
   doi = {10.21125/edulearn.2018.1662},
   url = {http://dx.doi.org/10.21125/edulearn.2018.1662},
   publisher = {IATED},
   location = {Palma, Spain},
   month = {2-4 July, 2018},
   year = {2018},
   pages = {7040-7044}
}

@inproceedings{Stolfi:2017:CNO:3071178.3071193,
   author = {Stolfi, Daniel H. and Alba, Enrique},
   title = {Computing New Optimized Routes for GPS Navigators Using Evolutionary Algorithms},
   booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference},
   series = {GECCO '17},
   year = {2017},
   isbn = {978-1-4503-4920-8},
   location = {Berlin, Germany},
   pages = {1240--1247},
   numpages = {8},
   url = {http://doi.acm.org/10.1145/3071178.3071193},
   doi = {10.1145/3071178.3071193},
   acmid = {3071193},
   publisher = {ACM},
   address = {New York, NY, USA},
   keywords = {application, evolutionary algorithm, real world, road traffic, smart city, smart mobility},
}

@InProceedings{ALCARAZ2017GAM,
   author = {Alcaraz, C. and Abdo, E. and Halir, R. and Toutouh, J. and Ruiz, M. and Stolfi, D.H.},
   title = {GAMIFICATION TO FIGHT LACK OF MOTIVATION AND HETEROGENEITY IN ENGINEERING},
   series = {9th International Conference on Education and New Learning Technologies},
   booktitle = {EDULEARN17 Proceedings},
   isbn = {978-84-697-3777-4},
   issn = {2340-1117},
   doi = {10.21125/edulearn.2017.1794},
   url = {http://dx.doi.org/10.21125/edulearn.2017.1794},
   publisher = {IATED},
   location = {Barcelona, Spain},
   month = {3-5 July, 2017},
   year = {2017},
   pages = {3662-3668}
}

@InProceedings{Stolfi2017,
   author    = {Stolfi, Daniel H. and Alba, Enrique and Yao, Xin},
   booktitle = {Smart Cities: Second International Conference, Smart-CT 2017, M{\'{a}}laga, Spain, June 14-16, 2017, Proceedings},
   title     = {Predicting Car Park Occupancy Rates in Smart Cities},
   year      = {2017},
   address   = {Cham},
   editor    = {Alba, Enrique and Chicano, Francisco and Luque, Gabriel},
   pages     = {107--117},
   publisher = {Springer International Publishing},
   doi       = {10.1007/978-3-319-59513-9_11},
   isbn      = {978-3-319-59513-9},
}

@inproceedings{Stolfi:2016:FTT:2908812.2908868,
   author = {Stolfi, Daniel H. and Armas, Rolando and Alba, Enrique and Aguirre, Hernan and Tanaka, Kiyoshi},
   title = {Fine Tuning of Traffic in Our Cities with Smart Panels: The Quito City Case Study},
   booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference 2016},
   series = {GECCO '16},
   year = {2016},
   isbn = {978-1-4503-4206-3},
   location = {Denver, Colorado, USA},
   pages = {1013--1019},
   numpages = {7},
   url = {http://doi.acm.org/10.1145/2908812.2908868},
   doi = {10.1145/2908812.2908868},
   acmid = {2908868},
   publisher = {ACM},
   address = {New York, NY, USA},
   keywords = {LED panels, application, evolutionary algorithm, real world, road traffic, smart city, smart mobility},
}

@InProceedings{Cintrano2016,
   author    = {Cintrano, Christian and Stolfi, Daniel H. and Toutouh, Jamal and Chicano, Francisco and Alba, Enrique},
   booktitle = {Smart Cities: First International Conference, Smart-CT 2016, M{\'{a}}laga, Spain, June 15-17, 2016, Proceedings},
   title     = {{CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentaly Friendly Routing Paths}},
   year      = {2016},
   address   = {Cham},
   editor    = {Alba, Enrique and Chicano, Francisco and Luque, Gabriel},
   pages     = {63--75},
   publisher = {Springer International Publishing},
   doi       = {10.1007/978-3-319-39595-1_7},
   isbn      = {978-3-319-39595-1},
}

@InProceedings{Stolfi2015,
   author    = {Stolfi, Daniel H. and Alba, Enrique},
   booktitle = {Advances in Artificial Intelligence},
   title     = {{An Evolutionary Algorithm to Generate Real Urban Traffic Flows}},
   year      = {2015},
   address   = {Cham},
   editor    = {Puerta, Jos{\'{e}} M and G{\'{a}}mez, Jos{\'{e}} A and Dorronsoro, Bernabe and Barrenechea, Edurne and Troncoso, Alicia and Baruque, Bruno and Galar, Mikel},
   pages     = {332--343},
   publisher = {Springer International Publishing},
   series    = {Lecture Notes in Computer Science},
   volume    = {9422},
   doi       = {10.1007/978-3-319-24598-0_30},
   isbn      = {978-3-319-24597-3},
   keywords  = {Evolutionary algorithm, SUMO, Smart city, Smart mobility, Traffic simulation, smart mobility},
}

@inproceedings{Stolfi:2015:SMP:2739480.2754742,
   author = {Stolfi, Daniel H. and Alba, Enrique},
   title = {Smart Mobility Policies with Evolutionary Algorithms: The Adapting Info Panel Case},
   booktitle = {Proceedings of the 2015 on Genetic and Evolutionary Computation Conference},
   series = {GECCO '15},
   year = {2015},
   isbn = {978-1-4503-3472-3},
   location = {Madrid, Spain},
   pages = {1287--1294},
   numpages = {8},
   url = {http://doi.acm.org/10.1145/2739480.2754742},
   doi = {10.1145/2739480.2754742},
   acmid = {2754742},
   publisher = {ACM},
   address = {New York, NY, USA},
   keywords = {application, evolutionary algorithm, led panels, road traffic, smart city, smart mobility},
}

@inproceedings{Stolfi2015:MAEB,
   address = {M\'{e}rida - Almendralejo},
   author = {Stolfi, Daniel H and Alba, Enrique},
   booktitle = {X Congreso Espa\~{n}ol sobre Metaheur\'{\i}sticas, Algoritmos Evolutivos y Bioinspirados},
   series = {MAEB 2015},
   keywords = {Algoritmo Evolutivo,Emisiones de gases,Movilidad Inteligente,Paneles LED,Tiempos de Viaje,Tr\'{a}fico Rodado},
   pages = {27--34},
   title = {{Un Algoritmo Evolutivo para la Reducci\'{o}n de Tiempos de Viaje y Emisiones Utilizando Paneles LED}},
   year = {2015},
   isbn = {978-84-697-2150-6}
}

@inproceedings{Stolfi:2014:ERT:2576768.2598317,
   author = {Stolfi, Daniel H. and Alba, Enrique},
   title = {Eco-friendly Reduction of Travel Times in European Smart Cities},
   booktitle = {Proceedings of the 2014 Conference on Genetic and Evolutionary Computation},
   series = {GECCO '14},
   year = {2014},
   isbn = {978-1-4503-2662-9},
   location = {Vancouver, BC, Canada},
   pages = {1207--1214},
   numpages = {8},
   url = {http://doi.acm.org/10.1145/2576768.2598317},
   doi = {10.1145/2576768.2598317},
   acmid = {2598317},
   publisher = {ACM},
   address = {New York, NY, USA},
   keywords = {application, evolutionary algorithm, gas emissions, road traffic, smart city, smart mobility, wifi connections},
}

@InProceedings{Stolfi2013,
   author    = {Stolfi, Daniel H. and Alba, Enrique},
   booktitle = {Advances in Artificial Intelligence},
   title     = {Reducing Gas Emissions in Smart Cities by Using the Red Swarm Architecture},
   year      = {2013},
   address   = {Berlin, Heidelberg},
   editor    = {Bielza, Concha and Salmer{\'o}n, Antonio and Alonso-Betanzos, Amparo and Hidalgo, J. Ignacio and Mart{\'i}nez, Luis and Troncoso, Alicia and Corchado, Emilio and Corchado, Juan M.},
   pages     = {289--299},
   publisher = {Springer Berlin Heidelberg},
   series    = {Lecture Notes in Computer Science},
   volume    = {8109},
   doi       = {10.1007/978-3-642-40643-0_30},
   isbn      = {978-3-642-40643-0},
   keywords  = {Application, Evolutionary Algorithm, Gas Emissions, Road Traffic, Smart City, Smart Mobility},
}

@inproceedings{Stolfi:2013:RSS:2463372.2463540,
   author = {Stolfi, Daniel H. and Alba, Enrique},
   title = {Red Swarm: Smart Mobility in Cities with EAS},
   booktitle = {Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation},
   series = {GECCO '13},
   year = {2013},
   isbn = {978-1-4503-1963-8},
   location = {Amsterdam, The Netherlands},
   pages = {1373--1380},
   numpages = {8},
   url = {http://doi.acm.org/10.1145/2463372.2463540},
   doi = {10.1145/2463372.2463540},
   acmid = {2463540},
   publisher = {ACM},
   address = {New York, NY, USA},
   keywords = {application, evolutionary algorithm, road traffic, smart city, smart mobility, wifi connections},
}