Mostrar el registro sencillo del ítem
Evolutionary Algorithms for Optimizing Emergency Exit Placement in Indoor Environments.
dc.contributor.author | Cotta-Porras, Carlos | |
dc.contributor.author | Gallardo-Ruiz, José Enrique | |
dc.date.accessioned | 2024-05-29T10:28:04Z | |
dc.date.available | 2024-05-29T10:28:04Z | |
dc.date.issued | 2024 | |
dc.identifier.citation | Cotta, C., Gallardo, J.E. (2024). Evolutionary Algorithms for Optimizing Emergency Exit Placement in Indoor Environments. In: Smith, S., Correia, J., Cintrano, C. (eds) Applications of Evolutionary Computation. EvoApplications 2024. Lecture Notes in Computer Science, vol 14634. Springer, Cham. https://doi.org/10.1007/978-3-031-56852-7_13 | es_ES |
dc.identifier.uri | https://hdl.handle.net/10630/31431 | |
dc.description | Política de acceso abierto tomada de: https://www.springernature.com/gp/open-research/policies/book-policies | es_ES |
dc.description.abstract | The problem of finding the optimal placement of emergency exits in an indoor environment to facilitate the rapid and orderly evacuation of crowds is addressed in this work. A cellular-automaton model is used to simulate the behavior of pedestrians in such scenarios, taking into account factors such as the environment, the pedestrians themselves, and the interactions among them. A metric is proposed to determine how successful or satisfactory an evacuation was. Subsequently, two metaheuristic algorithms, namely an iterated greedy heuristic and an evolutionary algorithm (EA) are proposed to solve the optimization problem. A comparative analysis shows that the proposed EA is able to find effective solutions for different scenarios, and that an island-based version of it outperforms the other two algorithms in terms of solution quality. | es_ES |
dc.description.sponsorship | Spanish Ministry of Science and Innovation under project Bio4Res (PID2021-125184NB-I00 - http://bio4res.lcc.uma.es) and by Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Springer Nature | es_ES |
dc.subject | Algoritmos evolutivos | es_ES |
dc.subject.other | Pedestrian Evacuation | es_ES |
dc.subject.other | Cellular Automata | es_ES |
dc.subject.other | Greedy Heuristics | es_ES |
dc.subject.other | Evolutionary Algorithms | es_ES |
dc.title | Evolutionary Algorithms for Optimizing Emergency Exit Placement in Indoor Environments. | es_ES |
dc.type | conference output | es_ES |
dc.centro | E.T.S.I. Informática | es_ES |
dc.relation.eventtitle | 27th International Conference on the Applications of Evolutionary Computation | |
dc.relation.eventplace | Aberystwyth (Reino Unido) | |
dc.relation.eventdate | 03/04/2024 | |
dc.identifier.doi | 10.1007/978-3-031-56852-7_13 | |
dc.type.hasVersion | SMUR | es_ES |
dc.departamento | Instituto de Tecnología e Ingeniería del Software de la Universidad de Málaga | |
dc.rights.accessRights | open access | es_ES |