Research on multi-objective fire station location algorithm based on risk classification

Yuanyuan Xue; Qize He

doi:10.1117/12.3005818

10 October 2023 Research on multi-objective fire station location algorithm based on risk classification

Yuanyuan Xue, Qize He

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127992N (2023) https://doi.org/10.1117/12.3005818
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

The previous selection and layout principles of fire stations in China were based on the principle that fire teams could reach the edge of their jurisdiction within 5 minutes in urban areas. This method did not consider the risk differences between regions and belonged to single-objective decision-making. This paper proposes a multi-objective fire rescue station location algorithm based on risk classification. The model takes the maximum weighted coverage rate as the objective function and the minimum coverage rate of the four risk levels as the constraint conditions. During the solving process, the final solution is selected as the one with the fewest number of fire stations among all feasible solutions that satisfy the constraint conditions. This model can ensure maximum coverage while achieving the minimum number of fire stations, and the constraint conditions can determine the minimum coverage rate of the solution, realizing multi-objective decision-making for fire station layout. This model has been applied in Xuhui District, Shanghai, and has shown good conformity to the actual situation.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuanyuan Xue and Qize He "Research on multi-objective fire station location algorithm based on risk classification", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127992N (10 October 2023); https://doi.org/10.1117/12.3005818

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