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Evolutionary Algorithms for Optimizing Emergency Exit Placement in Indoor Environments

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Applications of Evolutionary Computation (EvoApplications 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14634))

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.

This work is supported by 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.

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Notes

  1. 1.

    Note that since the perimeter is closed, the sum is to be understood as cycling back to 0 when reaching \(2(w+h)\).

  2. 2.

    https://github.com/Bio4Res/pedestrian-evacuation-optimization.

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Acknowledgments

The authors thank the Supercomputing and Bioinnovation Center (SCBI) of the University of Malaga for their provision of computational resources (the Picasso supercomputer http://www.scbi.uma.es).

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Authors and Affiliations

  1. Departamento Lenguajes y Ciencias de la Computación, ETSI Informática, Campus de Teatinos, Universidad de Málaga, 29071, Málaga, Spain

    Carlos Cotta & José E. Gallardo

  2. ITIS Software, Universidad de Málaga, Málaga, Spain

    Carlos Cotta & José E. Gallardo

Authors
  1. Carlos Cotta
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  2. José E. Gallardo
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Corresponding author

Correspondence to Carlos Cotta .

Editor information

Editors and Affiliations

  1. University of York, York, UK

    Stephen Smith

  2. University of Coimbra, Coimbra, Portugal

    João Correia

  3. University of Málaga, Málaga, Spain

    Christian Cintrano

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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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

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  • DOI: https://doi.org/10.1007/978-3-031-56852-7_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-56851-0

  • Online ISBN: 978-3-031-56852-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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