Multi-modal multi-target emergency material dispatching optimization method

Through the multi-modal multi-objective optimization algorithm of local center declustering, the problem of inappropriate site selection of material dispatch nodes in emergency material scheduling is solved, and more efficient material scheduling is achieved in emergency situations, providing more appropriate transit point site selection information, and improving emergency response capabilities.

CN120430438APending Publication Date: 2025-08-05ZHENGZHOU UNIV
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Patent Information

Application Number
CN202410632759.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-05-21
Publication Date
2025-08-05

AI Technical Summary

Technical Problem

In emergency material scheduling, it is difficult for the existing technology to effectively select and set up sufficient number and suitable material scheduling nodes, resulting in delays in rescue response time and affecting rescue efficiency and effect.

Method used

A multimodal multi-objective optimization algorithm based on local center declustering is adopted to establish an emergency transit point site selection optimization model. Through the local center decluttering mechanism and adaptive local search strategy, the global and local optimal transit point site selection location is found to ensure the comprehensive optimization of the number of demand points and emergency priority within the coverage range.

Benefits of technology

It improves the flexibility and efficiency of emergency material scheduling, can provide more appropriate transit point site selection information in complex and changing emergency situations, and provides decision makers with more flexible scheduling solutions to reduce rescue delays and losses.

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Abstract

The invention discloses a multi-modal multi-target emergency material scheduling optimization method. The method comprises the following steps: step 1, establishing an emergency transit point site selection optimization model; when emergency materials need to be transported from a transit point to a demand point, the materials at the transit point can be sent to the demand point as soon as possible in a coverage range of scheduling resources, and the covered demand point has a relatively high emergency priority level; 2, performing preliminary calculation on the model established in the step 1 to obtain the overall coverage rate of the transfer points to the demand points and the average material delivery time from the alternative transfer points to all the demand points; and step 3, solving the model by adopting a multi-modal multi-objective optimization algorithm based on local center declustering. According to the method, basic problem modeling is carried out on the site selection problem of the transit point, the problem is solved by using a multi-modal multi-objective optimization algorithm based on local center declustering, and a plurality of local optimal site selection positions can be provided while the global optimal site selection position is found.
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