Optimization On The Helicopters And Vehicles Intermodal Transportation Of Emergency Medical Supplies

In response to large-scale disasters, the reasonable allocation and quick transportation of medical supplies take an important role in enhancing the efficiency and effectiveness of life rescue in affected areas. Different disaster situations need corresponding allocation and transportation methods. In this thesis, we focus on a kind of disaster response situations:In large-scale disasters, due to the long distance among supply nodes and demand nodes or the cut off of key roads to affected areas, after allocating the available medical supplies in large collecting and distributing hub (LCDH) to medical aid points (MAPs), emergency decision-makers use helicopters at the LCDH to transport medical supplies to emergency distribution points (EDPs) and then use vehicles at EDPs to transit the received medical supplies to MAPs. Focusing the allocation and intermodal transportation of medical supplies under above disaster situations, in this thesis we have made the following three contributions:The first contribution is to investigate the situation-based allocation method of medical supplies in large-scale disasters respectively with complete and incomplete information. At the response stage, it is difficult or impossible to collect enough supplies under short preparation and pressing response time. Thus, the available relief supplies are often proportionately allocated to affected areas in different situations. Meanwhile, emergency decision-makers often consider multiple factors for allocating relief supplies to MAPs, and the information on these factors is not always precise. Considering the relative scarcity of medical supplies, the lack of historical data and the heterogeneity of influencing factors, we formulate the situation-based relative similarity to develop an allocation method of medical supplies with complete situation information. The method could allocate available medical supplies to MAPs with complete situations in proportions which are consistent with the facing situations. Considering the decision preferences, we further develop the situation-based allocation method of medical supplies with interval and fuzzy information which could allocate available medical supplies when the situations of MAPs are a mixture of crisp, interval and fuzzy information. By random numerical experiments, the effectiveness and advantage of the proposed methods are verified in comparison with the results by extant methods.Secondly, we investigate efficiency-targeted model and algorithm of emergency medical supply intermodal transportation, and then extend them to balanced models and algorithms To be specific, we propose a FCM-based approach of selecting EDPs and partitioning MAPs, and build a clustering-based model of optimizing medical supply intermodal transportation routes, which could respectively construct the intermodal transportation network and produce the intermodal routes from the LCDH to EDPs finally to MAPs; Meanwhile, in order to measure the efficiency and effectiveness of intermodal transportation, we construct three performance metrics:total extra capacity (TEC), average waiting time (AWT) and biggest waiting time (BWT). What is more, we consider capacity constrains to propose an FCMwCC-based method which could balance the extra capacity in each partitioning as much as possible, and consider the number constrains of MAPs to propose an FCMwNC-based method which could effectively balance the number of MAPs in each partitioning. Simulations verify that the FCMwCC-based method could enhance the use efficiency of medical vehicles, and the FCMwNC-based method could shorten the AWT and BWT of intermodal transportation.The third contribution is to study the recovery model and algorithm for the disruption of changed EDPs in emergency medical supply intermodal transportation. The development and occurrence of original and secondary disasters may disable existing EDPs, and the further rescue may produce new EDPs. These changed EDPs will bring about disturbance to the original plan of intermodal transportation which often needs to be adjusted accordingly. In this thesis, we consider supply arrival time, intermodal transportation route and used transportation capacity to measure the disruptions, develop a recovery model for emergency medical supplies intermodal transportation with changed EDPs, and design an improved genetic algorithm by applying new customer-based coding method and simplification-based population initialization method. Numerical simulations are conducted to verify the effectiveness of the proposed model and improved algorithm, and show the advantage of disruption management over the rescheduling method. This study also presents a new research issue for logistics disruption management, that is, the disruption management of intermodal transportation.This thesis is of specific academic and practical significance. The presented situation-based methods of allocating medical supplies could provide a new way to allocate emergency resources in response to disasters under both complete and incomplete situations. The developed models and algorithms of emergency medical supply intermodal transportation as well as their disruption management method could contribute a further development to theories and methods of emergency logistics optimization and disruption management.