Emergency Logistics Vehicle Routing Optimization Model under Uncertain Environment

Baiquan Li () and Baocheng Ding
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Baiquan Li: Liaoning Technical University, School of Business Administration
Baocheng Ding: Liaoning Technical University, School of Business Administration

A chapter in Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024), 2024, pp 954-962 from Springer

Abstract: Abstract Against the background of public health events, in the face of demand uncertainty, it is necessary to rationally plan emergency logistics routes to ensure the timely delivery of supplies to disaster-affected areas. Taking a certain area in Wuhan during the epidemic as an example, it was found that there was a lack of reasonable planning for emergency material routes, and the urgency of service at disaster-affected points was not considered during material distribution. An analysis of demand urgency was conducted to address this issue, and a service urgency model was constructed. Simultaneously, a linear goal planning model was established with vehicle distance cost, penalty cost, and fixed operating cost as the objective functions, and with constraints such as vehicle load capacity, delivery time windows, and material demand urgency. The genetic algorithm was employed to solve the model. An example was used to demonstrate the effectiveness of the vehicle routing model considering the urgency of emergency material services.

Keywords: Emergency Logistics; Demand Urgency; Path Optimization (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-570-6_95

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