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A Discrete Inspired Bat Algorithm for Firetruck Dispatch in Emergency Situations

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Part of the Springer Tracts in Civil Engineering book series (SPRTRCIENG)

Abstract

This research considers the case where a large fire has developed beyond the possibility of suppression and resources need to be deployed to reduce the risk to critical assets. Thus, to determine an optimal deployment of the firetrucks to multiple assets in a large area, a mathematical formulation is proposed, focusing on the maximization of the aggregated value of the protected assets that are critically selected, and on the minimization of the dispatch strategy cost. Moreover, the novelty of the presented formulation is the incorporation of the CO2 emissions of the firetrucks in the cost function, and, hence, the formulation of the Green-Prize Collecting Vehicle Routing Problem. Moreover, a hybrid Bat Algorithm (BA) is developed for the optimization of the aforementioned problem, namely the Discrete Inspired Bat Algorithm (DIBA). The effectiveness of the proposed algorithmic approach is demonstrated over computational experiments, in comparison with the results of a commercial exact solver.

Keywords

  • Discrete bat algorithm
  • Prize-collecting vehicle routing problem
  • CO2 emissions

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Fig. 10.1

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Acknowledgements

This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme “Human Resources Development, Education and Lifelong Learning” in the context of the project “Strengthening Human Resources Research Potential via Doctorate Research” (MIS-5000432), implemented by the State Scholarships Foundation (IKY).

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Correspondence to Dimitra Trachanatzi .

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Trachanatzi, D., Rigakis, M., Marinaki, M., Marinakis, Y. (2020). A Discrete Inspired Bat Algorithm for Firetruck Dispatch in Emergency Situations. In: Gocić, M., Aronica, G., Stavroulakis, G., Trajković, S. (eds) Natural Risk Management and Engineering. Springer Tracts in Civil Engineering . Springer, Cham. https://doi.org/10.1007/978-3-030-39391-5_10

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  • DOI: https://doi.org/10.1007/978-3-030-39391-5_10

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