Optimization Of Emergency Blood Transferring Problem In Unconventional Emergencies

All kinds of unconventional emergencies with serious impacts occasionally happen in the world, including earthquakes, big terrorism attacks and other events that always result in a large number of casualties. As a special kind of relief material, the important role blood plays in emergency rescue. To cope with the sharp rise in demand for blood in emergency, emergency transferring of blood from unaffected area is required when blood inventory and donations in disaster area can not satisfy the clinical demands.Blood relief is directly related to the lives of the injured people, so it is of great social significance to research on emergency blood transferring problems in unconventional emergencies. During emergency blood relief, rational decision shall be made for the selection blood banks in emergency service, and how many blood quantities distributed to each affected blood bank shall be determined; multimodal transportation routes shall be optimized; and timely transshipment of overstocked blood in affected blood banks shall be applied so as to reduce of the risk of outdate; when shortage of blood is inevitable during blood distribution, the substitution relations among each blood type shall be considered to reach an optimization distribution plan of higher satisfaction.Main research contents in the paper are as follows:(1) By analyzing the blood characteristics and phased characteristic of emergency blood support, as well as considering the impact of transportation mode on blood quality, a multi-stage optimization model of selection for blood banks in emergency service and allocation for emergency blood was developed for emergency blood transferring problem with multi-type blood products and multiple affected areas. A genetic algorithm with vector coding based on giving priority to key affected areas was proposed, with its time complexity analyzed. Finally, the model and algorithm were verified by a numerical example based on the emergency blood supply process in Wenchuan earthquake. The results show the high efficiency of proposed genetic algorithm and the superiority of proposed multi-stage decision-making method in indexes such as the freshness and overstock of blood.(2) Considering the physiological and emergency supply characteristics of blood, as well as multi-type blood and multi-modal transportation mode, a combined optimization model for blood banks in emergency service selection and transportation routing problem in emergency blood supply was developed based on a two-phase decision-making approach. The aim is to minimize the last arrival time, maximize the lowest average freshness when received, and minimize the total transportation cost of emergency blood. A hybrid genetic-tabu algorithm with local neighborhood search was proposed. The model and algorithm were verified by a numerical example with different scenarios of blood demand, which are built based on the emergency blood supply process in’5.12’Wenchuan earthquake. The results show that weight coefficients of the objective function and the demand forecasting error will affect the blood transferring solution, multi-modal transportation could increase the timeliness and efficiency of blood transferring. And the robustness of two-phase decision-making approach was confirmed by the comparison with one-phase decision-making approach on the indexes such as the last arrival time, the average freshness, the total transportation cost, and the overstock of blood.(3) By analyzing blood physiological characteristics, substitution relations and priority level among blood groups were determined. A bi-level programming model was developed for emergency blood distribution with multi-group blood products in multiple affected areas by considering substitution strategy. The upper model is to minimize the blood shortage as the goal, and the lower model is to minimize blood group substitution weight. On the premise of the consistency of the optimal solutions, the model was transformed into a mixed integer programming problem with a single objective. After ratiocinating the substitution nature of blood, a multi-phase greed heuristic algorithm was proposed with its time complexity analyzed. Finally, the model and algorithm were verified by a numerical example based on the emergency blood distribution process after Wenchuan earthquake. The influence of substitution rate on distribution scheme was analyzed, and the blood demand satisfaction improved by substitution strategy was proved. The results of different scale numerical examples show that the heuristic algorithm has high adaptability and calculation efficiency by comparing with CPLEX software.(4) By analyzing the blood inventory status and outdating characteristic, the age-based properties of transshipping and receiving was deduced, and a transshipment model was set up to minimize transport costs. Finally, effectiveness of reasoning model in the paper, difference between transfer strategies as well as support reliability coefficient, demand saturation coefficient, decision-making time and blood shelf life’s impacts on transshipment decision-making was confirmed through example simulation. All these results provided blood transshipment decision-making in emergency support with theoretical basis and referential examples.