Robust optimization approach to emergency mobile facility routing

Optimization of urban emergency support material distribution under major public health emergencies based on improved sparrow search algorithm

The outbreak of major public health emergencies such as the coronavirus epidemic has put forward new requirements for urban emergency management procedures. Accuracy and effective distribution model of emergency support materials, as an effective tool to inhibit the deterioration of the public health sector, have gradually become a research hotspot. The distribution of urban emergency support devices, under the secondary supply chain structure of "material transfer center-demand point," which may involve confusing demands, is studied to determine the actual situation of fuzzy requests under the impact of an epidemic outbreak. An optimization model of urban emergency support material distribution, based on Credibility theory, is first constructed. Then an improved sparrow search algorithm, ISSA, was designed by introducing Sobol sequence, Cauchy variation and bird swarm algorithm into the structure of the classical SSA. In addition, numerical validation and standard test set validation were carried out and the experimental results showed that the introduced improved strategy effectively improved the global search capability of the algorithm. Furthermore, simulation experiments are conducted, based on Shanghai, and the comparison with existing cutting-edge algorithms shows that the designed algorithm has stronger superiority and robustness. And the simulation results show that the designed algorithm can reduce vehicle cost by 4.83%, time cost by 13.80%, etc. compared to other algorithms. Finally, the impact of preference value on the distribution of emergency support materials is analyzed to help decision-makers to develop reasonable and effective distribution strategies according to the impact of major public health emergencies. The results of the study provide a practical reference for the solution of urban emergency support materials distribution problems.

Complex disaster response framework to reduce urban disaster vulnerability

Cities are vulnerable to a range of disasters that can occur simultaneously due to their complexity. Therefore, an effective disaster response plan is needed to reduce the disaster vulnerability of cities. In particular, evacuation route management is important for reducing the losses from a disaster. Efficient disaster response can be realized by searching for suitable evacuation routes and effective road network management. In this paper, we propose a disaster response framework based on a multilayered road network structure and evacuation routes based on our road network. The suggested road structure consists of three layers for the effective management of the network. An A* algorithm-based search for multiple evacuation routes under different conditions in response to an individual disaster on the configured road map provides a safe route for evacuees. As a result, the damage caused by disasters in urban areas can be ameliorated.

Optimization of Multi-Objective Mobile Emergency Material Allocation for Sudden Disasters

The mobile emergency system is a new emergency mode that provides a solution to deal with increasingly frequent sudden disasters by reasonably allocating mobile emergency facilities and optimizing the allocation of mobile emergency materials. We consider mobile emergency cost and mobile emergency time as two objective functions. This paper establishes a multi-objective mobile emergency material allocation model, and transforms the multi-objective. We choose the emergency material transportation path for coding, and apply the hybrid leapfrog algorithm for material allocation to obtain the optimal solution. Finally, the feasibility of the model is verified by taking Zhengzhou urban area under the “21.7” severe rainstorm and flood disaster in Henan Province. The result analyses show that the model can correspond to each stage of mobile emergency material allocation based on the value of cost preference, and put forward suggestions on the location of mobile emergency facilities and the amount of material allocation.