Research on Joint Optimization of Reserve and Dispatching for Multivariety Emergency Materials Based on NSGA-II
Emergency material reserve and dispatching are important measures to reduce casualties and property losses after natural disasters occur. However, there has not yet been research that optimizes both the reserve and distribution of emergency materials together. This paper investigates the joint optim...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/ddns/9990362 |
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| Summary: | Emergency material reserve and dispatching are important measures to reduce casualties and property losses after natural disasters occur. However, there has not yet been research that optimizes both the reserve and distribution of emergency materials together. This paper investigates the joint optimization of reserve and dispatching for multivariety emergency materials. Considering the timeliness, economy, and safety of emergency rescue, a multiobjective joint optimization model for emergency material reserve and dispatching has been established, with the targets of minimizing the total delay time, minimizing the total cost, and maximizing the number of safely delivered. Given the uncertainty in the emergency rescue, this paper uses interval numbers to represent transportation speed and triangular fuzzy numbers to represent transportation costs. Then, we study the model solution method, which mainly includes the conversion of uncertain constraints and the NSGA-II algorithm used for calculating the proposed multiobjective model. In the end, a numerical example is provided to demonstrate the validity and effectiveness of the proposed model and solution method. The results of the comparative analysis indicate that the comprehensive weighting strategy proposed in this paper is more balanced than the strategy that uses a single objective value as the optimization objective. |
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| ISSN: | 1607-887X |