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Grey-Theory-Based Optimization Model of Emergency Logistics Considering Time Uncertainty.
Bao-Jian Qiu1, Jiang-Hua Zhang2, Yuan-Tao Qi2
1School of Mathematical Sciences, University of Jinan, Jinan, Shandong China.
Plos One
|September 30, 2015
Summary
This study addresses complex emergency logistics challenges during natural disasters. It develops a method to select optimal paths, improving timely delivery of aid to affected areas.
Area of Science:
- Operations Research
- Disaster Management
- Logistics
Background:
- Natural disasters frequently cause significant casualties and property damage.
- Effective emergency logistics are crucial for disaster response.
- Existing models often struggle with uncertain path conditions and travel times.
Purpose of the Study:
- To address the multi-center, multi-commodity, single-affected-point emergency logistics problem.
- To develop a model that maximizes the time-satisfaction degree under uncertainty.
- To account for damaged paths and incomplete information in disaster logistics.
Main Methods:
- Established a nonlinear programming model with a time-satisfaction objective.
- Utilized grey theory to evaluate transportation network reliability.
- Selected optimal paths considering incomplete information and uncertain travel times.
- Simplified the model for single optimal path scenarios and solved using Lingo software.
Main Results:
- Successfully evaluated multiple transportation routes based on grey theory.
- Identified reliable and optimal paths for emergency logistics.
- Demonstrated the feasibility and effectiveness of the proposed method through numerical experiments.
Conclusions:
- The proposed method effectively handles uncertainty in emergency logistics.
- Optimized path selection enhances the timeliness of aid delivery.
- This approach provides a valuable tool for improving disaster response logistics.
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