Follow-up Sharing And Group Information Update-based Optimal Scheduling Of Resource Distribution For Post-earthquake Response

Earthquake has the characters of suddenness, pervasiveness, successiveness. A severe earthquake destroys the facilities and causes casualties at the same time, and induces secondary disasters and derivative disasters which will cause major destruction. The resource distribution for post-earthquake response is very important. Post-event response for earthquake is a complicated task with challenges of surging demand, uncertain supplies, and rough transportation in the face of infrastructure vulnerabilities. Therefore, resource distribution for post-event response after the earthquake is an uncertain planning problem to distribute many commodities to affected areas from distribution centers with multi-objectives, multi-constraints, multi-transportation mode and multi-transportation tool. Emergency planners need to make effective humanitarian logistics plans to efficiently allocate vehicles and relief resources under uncertain circumstances. Especially, they need to consider the follow-up sharing character (the subsequent phases should share part of former phases’ resources if previous phases’supplies were relatively surplus compared with the following phases’supplies) and group-information update. Based on the previous research, the resource distribution for post-earthquake response is studied by two different aspects:the follow-up sharing character, which coordinates resources between different phases; and group-information update, which makes the specific resource distribution plan just in time according the current information.Firstly, the resource distribution for post-earthquake response has the character of temporal continuity. It is necessary to coordinate the supplies between former phases and following phases to make the distribution plan more effective. To explain the effectiveness and efficiency of distribution plans, this paper addresses the resource allocation effectiveness losses (RAEL, the losses caused by the mismatch between supply and demand in impacted areas) and the emergency logistics time costs (ELTC, the time costs caused by logistics processes under emergency conditions). Considering the reality of resource distribution for post-earthquake response, the following phases can share parts of the former phases’resources, but the former phases cannot share any part of the following phases’resources (the follow-up sharing character). Therefore, based on FSC, this paper proposes an integrated model (IM) that aims to minimize RAEL and ELTC. The IM combines a time dimension model (TDM, which coordinates the phases of demands and supplies) and a space dimension model (SDM, which generates a specific distribution plan for the first phase). An analytical solution is proposed for TDM, whereas SDM is solved through a transportation programming model. The IM can be solved efficiently, which makes the proposed methodology fit the emergency circumstance well although the decision is time-constrained. Besides, a numerical simulation study is proposed to analyze the feasibility of this model.Secondly, unlike the normal logistics, emergency logistics in natural disasters is much more complicated. In emergency logistics planning, the information for decision-making is usually not complete and is updated every second. Besides, considering the dynamic and sequential process of post-earthquake resource distribution, the decision-making of emergency resources allocation in a natural disaster is a multi-phase process of "sampling-planning-dispatching". Therefore, both historical and current sample information are used to make effective plans in the proposed model by employing Bayesian information update approach. In this paper, a random variable is used to record historical and sample information for describing the road affected information. Besides, the allocation amount of each affected area is decided by the equity principle. On the base of this, a concept of transportation time cost due to logistics processes under emergency conditions is proposed. Therefore, by using Bayesian analysis theory and optimization theory, a sequential approach of "sampling-planning-dispatching" is proposed to guarantee the resources supply in the affected areas. In the solution approach, a matrix-coding-based genetic algorithm is developed to solve the model. Finally, a simulation study is conducted to verify the efficiency and effect of the proposed methodology.Finally, the uncertainty of earthquake brings the surging demand, uncertain supplies, and rough transportation time problems. There is absolutely a need to find a methodology to make effective and efficient distribution plans according to disaster, demand, supply and transportation information. Based on the Bayesian analysis theory, two losses are addressed to explain the influence of a disaster on supply, demand, and humanitarian logistics. The two losses include losses caused by the mismatch between supply and demand in affected areas and the time losses caused by logistics processes under emergency conditions. Considering the demand is related to population transfer status, and the transportation condition is related to the road damage level, a multi-period planning model with group information updates (GIU) is established based on the model without GIU using Bayesian theory. The established model describes a setting in which commodities are transported from dispatching centers to affected areas through multi-transportation modes of delivery in each emergency response period. Then, the model with GIU is revised into a single-objective model, and then a matrix-coding-based genetic algorithm is developed to solve the revised model. Finally, the proposed methodology is applied to the humanitarian logistics problems of emergency response encountered during the Wenchuan Earthquake in China. Computational results show that the proposed methodology can generate specific logistics plans for allocating relief resources according to updated information.