The impact of Mean Time Between Disasters on inventory pre-positioning strategy

Purpose - This paper addresses the impact of Mean Time Between Disasters (MTBD) to inventory pre-positioning strategy of medical supplies prior to a sudden-onset disaster

Collaborative Prepositioning Network Design for Regional Disaster Response

We present a collaborative prepositioning strategy to strengthen the disaster preparedness of the Caribbean countries, which are frequently hit by hurricanes. Since different subsets of countries are affected in each hurricane season, significant risk pooling benefits can be achieved through horizontal collaboration, which involves joint ownership of prepositioned stocks. We worked with the intergovernmental Caribbean Disaster and Emergency Management Agency to design a collaborative prepositioning network in order to improve regional response capacity. We propose a novel insurance-based method to allocate the costs incurred to establish and operate the proposed collaborative prepositioning network among the partner countries. We present a stochastic programming model, which determines the locations and amounts of relief supplies to store, as well as the investment to be made by each country such that their premium is related to the cost associated with the expected value and the standard deviation of their demand. We develop a realistic data set for the network by processing real-world data. We conduct extensive numerical analyses and present insights that support practical implementation. We show that a significant reduction in total inventory can be achieved by applying collaborative prepositioning as opposed to a decentralized policy. Our results also demonstrate that reducing the replenishment lead time during the hurricane season and improving sea connectivity are essential to increasing the benefits resulting from the network.TÜBİTAK ; Institute for Data Valorisation (IVADO) ; Natural Sciences and Engineering Research Council of Canad

Stochastic network models for logistics planning in disaster relief

Emergency logistics in disasters is fraught with planning and operational challenges, such as uncertaintyabout the exact nature and magnitude of the disaster, a lack of reliable information about the locationand needs of victims, possible random supplies and donations, precarious transport links, scarcity ofresources, and so on. This paper develops a new two-stage stochastic network flow model to help decidehow to rapidly supply humanitarian aid to victims of a disaster within this context. The model takesinto account practical characteristics that have been neglected by the literature so far, such as budgetallocation, fleet sizing of multiple types of vehicles, procurement, and varying lead times over a dynamicmultiperiod horizon. Attempting to improve demand fulfillment policy, we present some extensions ofthe model via state-of-art risk measures, such as semideviation and conditional value-at-risk. A simpletwo-phase heuristic to solve the problem within a reasonable amount of computing time is also suggested.Numerical tests based on the floods and landslides in Rio de Janeiro state, Brazil, show that the modelcan help plan and organise relief to provide good service levels in most scenarios, and how this dependson the type of disaster and resources. Moreover, we demonstrate that our heuristic performs well for realand random instances

Disaster preparedness in humanitarian logistics:A collaborative approach for resource management in floods

The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency. Consequently, successful operations rely heavily on the collaboration of different organisations. Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence. This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities. The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities

Relief distribution networks : a systematic review

In the last 20 years, Emergency Management has received increasing attention from the scientific community. Meanwhile, the study of relief distribution networks has become one of the most popular topics within the Emergency Management field. In fact, the number and variety of contributions devoted to the design or the management of relief distribution networks has exploded in the recent years, motivating the need for a structured and systematic analysis of the works on this specific topic. To this end, this paper presents a systematic review of contributions on relief distribution networks in response to disasters. Through a systematic and scientific methodology, it gathers and consolidates the published research works in a transparent and objective way. It pursues three goals. First, to conduct an up-to-date survey of the research in relief distribution networks focusing on the logistics aspects of the problem, which despite the number of previous reviews has been overlooked in the past. Second, to highlight the trends and the most promising challenges in the modeling and resolution approaches and, finally, to identify future research perspectives that need to be explored

Effective prepositioning of relief inventory for humanitarian operations in the Central African Region

Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2023.Inventory management is a crucial aspect of humanitarian operations. Various inventory models and policies have been developed over the years to improve the efficiency of humanitarian inventory management. These models consider various elements, including sourcing, storage, prepositioning, distribution, and transportation. While the existence of literature and models supplied guidance and breakthroughs towards more informed decision-making, the complex setting of disasters has continued to preclude their application. Over-simplification, impracticality, and particularity of decision variables pose a challenge in using specific models in exceptionally distinct disasters owing to their complexity and ever-changing nature. This implies that the ability to manage inventory efficiently and its distribution depends on the preparedness and prevailing conditions in the post disaster period. This study focused on approaching these shortcomings by adopting an integrated approach which starts with the characterisation of inventory management challenges unique to disaster settings. Gaps within developed models are identified, and an inventory prepositioning and aid distribution model is developed and applied to bridge some gaps. Therefore, this study presents two models (deterministic and stochastic programming with recourse) for prepositioning modelling. The models are implemented as multi-objective mixed-integer linear programming relief inventory prepositioning models for the Democratic Republic of Congo (DRC) and Central African Republic (CAR). The models minimise shortages and enhance equitability while minimising the total response time in areas with poor road network in a cross-border distribution setting. The model is solved using a pre-emptive optimisation approach, and a sensitivity analysis is conducted to evaluate the influence of the budget, priority items proportion, and capacity variation in the model input. Results indicate that the models are sensitive to changing parameters. Of the two models, the stochastic model was determined to have higher reliability but required a higher budget to match the performance of the deterministic model. Results analyses confirm that the models can add value to humanitarian organisations when planning facility locations, inventory prepositioning, and conflict area-distribution centre assignments in the DRC and CAR. This study, therefore, contributes to the body of knowledge and humanitarian organisations in Africa.Industrial and Systems EngineeringMEng (Industrial Engineering)Unrestricte

Toward resilient humanitarian cooperation: examining the performance of horizontal cooperation among humanitarian organizations using an agent-based modeling (ABM) approach

This article proposes a multi-agent simulation model to examine how different operational environments and incentive mechanisms affect the collective performance of complex humanitarian response systems. Using the UN Humanitarian Response Depot (UNHRD) system as an example, a stylized model of one service provider, two member organizations and multiple humanitarian crises is developed to illustrate the changing uses of four alternative relief goods sourcing options, namely: i) own storage for own items ii) UN storage for own items iii) stock-swaps and iv) white stock uses. Under the plausible assumption that the past success of sourcing options influences member organizations' future resource allocation, the model indicates that the additional buffer stock capacity offered by horizontal cooperation induces undesirable system dependency: while it gives member organizations more flexibility to meet highly stochastic demands under uncertainty, it also encourage them to store less of their own relief goods as a result. This tendency was particularly notable under a flexible budgeting regime, highlighting the further need to understand and evaluate the details of the decision-making heuristics of individual member organizations

A Stochastic Capacitated Facility Location Model For Pre-Positioning Port Commodities During A Disaster

As the intensity of natural disasters increases, there is a need to develop policies and procedures to assist various humanitarian relief groups, industry or government agencies with moving aid to affected areas. One of the biggest hindrances to this process is damage to transportation networks, in particular, waterways. To keep waterways safe, aids to navigation (ATONs) are placed in various areas to guide mariners and ships to their final destinations. If the ATONs are damaged, then the waterways are left unsafe and it is difficult to move supplies to repair them and recover from a disaster. A stochastic facility location model is presented to understand the advantage of prepositioning repair supplies in order to maximize the repair of ATONs. The first stage decisions focus on location determination of resources that are prepositioned. The second stage decisions consist of the distribution of supplies and teams to affected areas. The results will show the benefits of a prepositioning policy toward the responsiveness of restoring waterway

Decision-making and operations in disasters: challenges and opportunities

Decision-making structures are commonly associated with the logistics challenges experienced during disaster operations. However, the alignment between the operational level and the decision-making structure is commonly overlooked. The purpose of this research is to provide an analysis of the fit of both levels and its impact on performance. The research is developed around a case study in Mexico. Through a review of the disaster management policy in the country, interviews, and secondary data, the article provides an analysis of the current decision-making structure, the logistics activities undertaken by authorities and the impact of the alignment between both components on logistics performance. The analysis suggests that several of the challenges commonly associated centralisation are actually rooted on its alignment with the operational level. Logistics performance is negatively affected by faulty assumptions, poorly planned procedures, inconsistent decision-making, and poorly designed structures. The case showed the need to align the operational level with a centralised perspective to increase responsiveness, flexibility and the interaction between different organisations. This article identifies the impact of the misalignment between the decision-making structure and the operational level on logistics performance, an area currently understudied. It moves from the current argument about the appropriate decision-making structure for disaster management to the identification of components to implement an efficient and effective disaster management system. Additionally, this paper provides recommendations for best practices in humanitarian logistics which are applicable to Mexico and other countries using a centralised decision-making approach