Dra. Gema Bello Orgaz

@inproceedings{pedemonte2020exploring,

title = {Exploring multi-objective cellular genetic algorithms in community detection problems},

author = {Martín Pedemonte and Ángel Panizo-LLedot and Gema Bello-Orgaz and David Camacho},

doi = {10.1007/978-3-030-62365-4_22},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

booktitle = {International Conference on Intelligent Data Engineering and Automated Learning},

pages = {223--235},

organization = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{panizo2019describing,

title = {Describing alt-right communities and their discourse on twitter during the 2018 us mid-term elections},

author = {Ángel Panizo-LLedot and Javier Torregrosa and Gema Bello-Orgaz and Joshua Thorburn and David Camacho},

doi = {10.1007/978-3-030-36683-4_35},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

booktitle = {International conference on complex networks and their applications},

pages = {427--439},

organization = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{panizo2018genetic,

title = {A genetic algorithm with local search based on label propagation for detecting dynamic communities},

author = {Ángel Panizo-LLedot and Gema Bello-Orgaz and David Camacho},

doi = {10.1007/978-3-319-99626-4_28},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

booktitle = {International symposium on intelligent and distributed computing},

pages = {319--328},

organization = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{panizo2018community,

title = {Community finding in dynamic networks using a genetic algorithm improved via a hybrid immigrants scheme},

author = {Ángel Panizo-LLedot and Gema Bello-Orgaz and Alfonso Ortega and David Camacho},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

booktitle = {Data Science and Knowledge Engineering for Sensing Decision Support: Proceedings of the 13th International FLINS Conference (FLINS 2018)},

pages = {591--598},

organization = {World Scientific},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{panizo2018artificial,

title = {An Artificial Bee Colony algorithm for optimizing the design of sensor networks},

author = {Ángel Panizo-LLedot and Gema Bello-Orgaz and Mercedes Carnero and José Hernández and Mabel Sánchez and David Camacho},

doi = {10.1007/978-3-030-03496-2_35},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

booktitle = {International Conference on Intelligent Data Engineering and Automated Learning},

pages = {316--324},

organization = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{panizo2018algoritmo,

title = {Un Algoritmo Memético, con búsqueda local basada en Label Propagation, para detectar comunidades en redes dinámicas},

author = {Ángel Panizo-LLedot and Gema Bello-Orgaz and Alfonso Ortega and David Camacho},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

booktitle = {XVIII Conferencia de la Asociación Espa~nola para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, Espa~na},

pages = {995--1000},

organization = {Asociación Espa~nola para la Inteligencia Artificial (AEPIA)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Ramirez-Atencia2016a,

title = {A Weighted Penalty Fitness for a Hybrid MOGA-CSP to solve Mission Planning Problems},

author = {Cristian Ramirez-Atencia and Gema Bello-Orgaz and Maria D R-Moreno and David Camacho},

url = {http://aida.etsisi.upm.es/wp-content/uploads/2017/03/A-Weighted-Penalty-Fitness-for-a-Hybrid-MOGA-CSP-to-solve-Mission-Planning-Problems.pdf},

year  = {2016},

date = {2016-01-01},

urldate = {2016-01-01},

booktitle = {XI Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2016)},

pages = {305--314},

abstract = {Unmanned Aerial Vehicles (UAVs) are currently booming due to their high number of potential applications. In Mission Planning problems, several tasks must be performed by a team of UAVs, under the supervision of one or more Ground Control Stations (GCSs). In our approach, we have modelled the problem as a Constraint Satisfaction Problem (CSP), and solved it using a Multi-Objective Genetic Algorithm (MOGA). The algorithm has been designed to minimize several variables of the mission such as the fuel consumption or the makespan. In addition, the fitness function takes a new consideration when solutions are not valid. It uses the number of constraints fulfilled for each solution as a weighted penalty function. In this way, the number of constraints fulfilled is maximized in the elitism phase of the MOGA. Results show that the approach outperforms the convergence with respect to previous results.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Ramirez-Atencia2016b,

title = {MOGAMR: A Multi-Objective Genetic Algorithm for Real-Time Mission Replanning},

author = {Cristian Ramirez-Atencia and Gema Bello-Orgaz and Maria D R-Moreno and David Camacho},

doi = {10.1109/SSCI.2016.7850235},

isbn = {978-1-5090-4240-1, 978-1-5090-4241-8},

year  = {2016},

date = {2016-01-01},

booktitle = {2016 IEEE Symposium Series on Computational Intelligence (SSCI)},

abstract = {From the last few years the interest and repercussion on Unmanned Aerial Vehicle (UAV) technologies have been extended from pure military applications to industrial and societal applications. One of the basic tasks to any UAV problems is related to the Mission Planning. This problem is particularly complex when a set of UAVs is considered. In the field of MultiUAV Mission Planning, some approaches have been carried out in the last years. However, there are few works related to realtime Mission Replanning, which is the focus of this work. In Mission Replanning, some changes in the mission, such as the arrival of new tasks, require to update the preplanned solution as fast as possible. In this paper a Multi-Objective Genetic Algorithm for Mission Replanning (MOGAMR) is proposed to handle this problem. This approach uses a set of previous plans (or solutions), generated using an offlline planning process, in order to initialize the population of the algorithm, then acts as a complete regeneration method. In order to simulate a real-time system we have fixed a time limit of 2 minutes. This has been considered as an appropriate time for a human operator to take a decision. Using this time restriction, a set of experiments adding from 1 to 5 new tasks in the Replanning Problems has been carried out. The experiments show that the algorithm works well with this few number of new tasks during the replanning process generating a set of feasible solutions under the time restriction considered.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ramirez2015hybrid,

title = {A Hybrid MOGA-CSP for Multi-UAV Mission Planning},

author = {Cristian Ramirez-Atencia and Gema Bello-Orgaz and María D R-Moreno and David Camacho},

url = {http://aida.etsisi.upm.es/wp-content/uploads/2015/09/ramirez-atenciaHybrid.pdf},

year  = {2015},

date = {2015-01-01},

booktitle = {Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference},

pages = {1205--1208},

organization = {ACM},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/iccci/Ramirez-Atencia15,

title = {Performance Evaluation of Multi-UAV Cooperative Mission Planning Models},

author = {Cristian Ramírez-Atencia and Gema Bello-Orgaz and Maria D R-Moreno and David Camacho},

url = {http://dx.doi.org/10.1007/978-3-319-24306-1_20 

http://aida.etsisi.upm.es/wp-content/uploads/2015/09/ramirez-atenciaPerformance.pdf},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

booktitle = {Computational Collective Intelligence - 7th International Conference, ICCCI 2015, Madrid, Spain, September 21-23, 2015, Proceedings, Part II},

pages = {203--212},

crossref = {DBLP:conf/iccci/2015-2},

abstract = {The Multi-UAV Cooperative Mission Planning Problem (MCMPP) is a complex problem which can be represented with a lower or higher level of complexity. In this paper we present a MCMPP which is modelled as a Constraint Satisfaction Problem (CSP) with 5 increasing levels of complexity. Each level adds additional variables and constraints to the problem. Using previous models, we solve the problem using a Branch and Bound search designed to minimize the fuel consumption and number of UAVs employed in the mission, and the results show how runtime increases as the level of complexity increases in most cases, as expected, but there are some cases where the opposite happens.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ramirez2014solving,

title = {Solving UAV Mission Planning based on Temporal Constaint Satisfaction Problem using Genetic Algorithms},

author = {Cristian Ramirez-Atencia and Gema Bello-Orgaz and Maria D R-Moreno and David Camacho},

year  = {2014},

date = {2014-09-12},

urldate = {2014-09-12},

booktitle = {Doctoral Program Proceedings of The 20th International Conference on Principles and Practice of Constraint Programming (CP 2014)},

abstract = {The problem of Mission Planning for a large number of Unmanned Air Vehicles (UAV) consists of a set of locations to visit in different time windows, and the actions that the vehicle can perform based on its features such as the payload, speed or fuel capacity. We study how this problem can be formulated as a Temporal Constraint Satisfaction Problem (TCSP). This problem contains several constraints assuring UAVs are assigned to tasks they have enough characteristics to perform, and soft-constraints for optimizing the time and fuel spent in the process. Our goal is to implement this model and then try to solve it using Genetic Algorithms (GAs). For this purpose, we will carry out a mission simulation containing m UAVs with different sensors and characteristics located in different waypoints, and n requested tasks varying mission priorities. The GA will match the model constraints and use a multi-objective function in order to minimize the cost.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{bello2014evolutionary,

title = {Evolutionary clustering algorithm for community detection using graph-based information},

author = {Gema Bello-Orgaz and David Camacho},

url = {http://aida.etsisi.upm.es/wp-content/uploads/2014/12/CEC14_BelloOrgaz-Camacho.pdf},

year  = {2014},

date = {2014-01-01},

booktitle = {Evolutionary Computation (CEC), 2014 IEEE Congress on},

pages = {930--937},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ramirez2014simple,

title = {A simple CSP-based model for unmanned air vehicle mission planning},

author = {Cristian Ramirez-Atencia and Gema Bello-Orgaz and Maria D R-Moreno and David Camacho},

year  = {2014},

date = {2014-01-01},

urldate = {2014-01-01},

booktitle = {2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings},

pages = {146--153},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ramirez2014branching,

title = {Branching to find feasible solutions in unmanned air vehicle mission planning},

author = {Cristian Ramirez-Atencia and Gema Bello-Orgaz and Maria D R-Moreno and David Camacho},

year  = {2014},

date = {2014-01-01},

urldate = {2014-01-01},

booktitle = {International Conference on Intelligent Data Engineering and Automated Learning},

pages = {286--294},

organization = {Springer, Cham},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Orgaz:2012:CAB:2189736.2189743,

title = {Clustering avatars behaviours from virtual worlds interactions},

author = {Gema Bello-Orgaz and Maria D R-Moreno and David Camacho and David F Barrero},

url = {http://doi.acm.org/10.1145/2189736.2189743},

issn = {978-1-4503-1189-2},

year  = {2012},

date = {2012-01-01},

urldate = {2012-01-01},

booktitle = {Proceedings of the 4th International Workshop on Web Intelligence & Communities},

pages = {4:1--4:7},

publisher = {ACM},

address = {New York, NY, USA},

series = {WI&C '12},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Menendez:2012:FSH:2254129.2254155,

title = {Features selection from high-dimensional web data using clustering analysis},

author = {Héctor D Menéndez and Gema Bello-Orgaz and David Camacho},

url = {http://doi.acm.org/10.1145/2254129.2254155},

issn = {978-1-4503-0915-8},

year  = {2012},

date = {2012-01-01},

urldate = {2012-01-01},

booktitle = {Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics},

pages = {20:1--20:9},

publisher = {ACM},

address = {New York, NY, USA},

series = {WIMS '12},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{BelloCajiasCamacho2011,

title = {Study on the Impact of Crowd-Based Voting Schemes in the ’Eurovision’ European Contest},

author = {Gema Bello-Orgaz and Raul Cajias and David Camacho},

url = {http://dl.acm.org/citation.cfm?id=1988718 

http://aida.etsisi.upm.es/wp-content/uploads/2012/09/WIMS2011AStudyOnImpact.pdf},

year  = {2011},

date = {2011-01-04},

urldate = {2011-01-04},

booktitle = {1st International Conference on Web Intelligence, Mining 

and Semantics (WIMS’11)},

publisher = {ACM Press},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}