Stockpiling Decisions Of Relief Materials

It is commonly seen that a relief organization employs relief materials’ reservation to respond potential disaster events. Preparation of relief materials plays an important role in quickly and efficiently satisfying the sufferers’ demands, as well as in realizing the prevention-oriented methodology of disaster alleviation, which is emphasized by the Chinese central government. However, stockpiling relief materials could be very risky due to the uncertainties of disaster events and materials’ demands. Too much relief inventories could incur low economic efficiency for materials’ preparedness. Hence, we should balance the necessity and risk of materials’ reservation and then develop some efficient methods to determine a proper stockpiling quantity. The extant related literature pays much attention on emergency resources’ scheduling decision, while the stockpiling decisions of relief materials are always ignored. Therefore, studies of relief materials’ stockpiling have significant theoretical and practical values.The dissertation focuses on three problems. First, how to characterize the demands of relief materials at the stage of disaster preparedness on the basis of the uncertainties of disaster events and materials’ demands. Second, given all relief demands should be fully satisfied, how to establish models to determine the optimal stockpiling quantity of single and multiple product relief materials’. Specifically, how to determine the quantity of reservations of a variety of relief materials when a budget constraint exists? The last one is that whether there exist some appropriate flexible reserve policies can improve the performance of stockpiling of relief materials. To solve the three problems, the dissertation is organized as six chapters. Chapter 1 is the introductive part where the motivation, literature review, content, academic value and structure are presented. Chapter 2 establishes the relief stockpiling decision model of a single-product. The multi-product decision models with and without a budget constraint are developed in Chapter 3. Chapter 4 proposes two flexible stockpiling policies for a single product’s:Agreement relief storage (ARS) and option relief storage (ORS) policies. The former indicates that the relief organization and the supplier jointly stockpile relief materials; while the latter implies that the relief organization employs an option contract to incentivize the supplier’s storage. The multiproduct cases of flexible storage are investigated in Chapter 5. Chapter 6 provides the main conclusions and future directions.The dissertation obtains the following results:(1) We employ an approach combining the disaster event probability and stochastic distribution to characterize the uncertainties of the occurrence of disaster event and materials’demand. Under the framework of all incurred demands should be fully satisfied, we develop a (generalized) two-stage delivery process model to characterize relief materials’ delivery after a disaster. This result provides the theoretical basis for the following models.(2) Given the objective of all demands should be fully satisfied, we establish the stockpiling decision models of single product and multiple products relief materials. We also prove that these models have unique solutions. Moreover, this dissertation also develops a multi-product relief materials inventory model when a budget constraint is bound. The Karush-Kuhn-Tucker (KKT) condition is employed to solve the model. A binary method is developed and the computational examples demonstrate that the algorithm can converge to an arbitrary computational accuracy.(3) The dissertation models the ARS and ORS policies for the single product and multiple products stockpiling decision. Comparing with the non-flexible storage policy, we show that both flexible policies can increase the stockpiling quantity and decrease the total expected costs, which implies that the performance of relief storage is improved. Furthermore, we demonstrate that the ORS policy always dominates the ARS policy, which is commonly used in relief practices.