Stochastic Optimization Model for Ordering and Distribution of Emergency Medical Supplies Considering the Demand Uncertainty
Konferenz: CAIBDA 2022 - 2nd International Conference on Artificial Intelligence, Big Data and Algorithms
17.06.2022 - 19.06.2022 in Nanjing, China
Tagungsband: CAIBDA 2022
Seiten: 6Sprache: EnglischTyp: PDF
Autoren:
Chen, Zhuo; Cui, Na (School of Civil Engineering and Architecture, University of Jinan, Jinan, Shandong, China)
Inhalt:
Considering the uncertain demand of disaster affected areas under emergency conditions, a scenario-based two-stage stochastic program is established in this paper to explore a reliable emergency material pre-positioning and distribution plan. In the modeling framework, a series of pre-disaster and post-disaster concerns are incorporated, including the selection of emergency material suppliers for ordering contract with flexible quantities, pre-disaster allocation of materials in transfer warehouses, and post-disaster transportation of emergency materials respectively from warehouses and suppliers to deal with the uncertain demands of the disaster affected areas. Recycling redundant materials in the warehouse and reducing the unsatisfied demands of demand points are also considered in the optimization model. The model is coded in GAMS and CPLEX is used to get optimal results. A 30-node experimental road network is used for experimental analysis to verify the practicality of the proposed model and the rationality of the decision-making process.