Technical gazette, Vol. 33 No. 5, 2026.
Original scientific paper
https://doi.org/10.17559/TV-20260403003511
Optimization of Emergency Material Allocation in Flood Disasters Considering Demand Urgency
Xue Yan
; School of Business, Henan Forestry Vocational College, Luoyang, 471002, China
Ao Hou
; Sheqi Sub-branch, Henan Branch, China Construction Bank Corporation, Nanyang, 473300, China
Panke Zhang
; School of Business, Henan University of Science and Technology, Luoyang, 471000, China
*
* Corresponding author.
Abstract
Global warming has led to frequent extreme precipitation events, and regional flood disasters arising from this situation have posed severe challenges to public security and economic development. In the evolution of flood disasters, significant spatial-temporal heterogeneity is observed in different disaster-stricken regions. If heterogeneity of this kind is neglected, then the disaster points with high demand urgency cannot be given priority, thus missing the critical rescue window period. Incorporating the demand urgency of different disaster points into an emergency material allocation model plays a key role in improving disaster emergency performance. Aiming at the optimization of emergency material allocation in flood disasters, this study introduces the dimension of demand urgency evaluation to establish a complete set of decision models and methodology system. First, seven key indicators were selected from three dimensions: personnel, environment, and materials. A demand urgency evaluation system was built, and the urgency coefficient of each disaster point was calculated using the entropy weight-gray relation TOPSIS method. On this basis, an emergency material allocation multi-objective optimization model with time satisfaction, distribution fairness, and economic cost as the objectives was constructed. A hybrid intelligent optimization algorithm that combines particle swarm optimization and simulated annealing was designed to solve this complicated optimization problem, thus effectively improving solving efficiency and global optimization ability. With the extraordinary 7/20 rainstorm disaster in Zhengzhou taken as an empirical case, the results show that compared with the traditional scheme, the configuration scheme considering demand urgency improves the fairness indicator by 52.38% and reduces the total cost by 17%, verifying the marked advantages of this model in improving rescue efficiency, ensuring fairness, and controlling costs. The effects of different decision-making preferences on material allocation results were further discussed through sensitivity analysis of objective weights. The results provide decision-making support for emergency material allocation and are of great reference value for improving emergency rescue efficiency.
Keywords
demand urgency; emergency material allocation; flood disaster; optimization algorithm
Hrčak ID:
350418
URI
Publication date:
31.8.2026.
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