Disaster Relief Materials Research Articles

Community Resilience Assessment and Identification of Barriers in the Context of Population Aging: A Case Study of Changchun City, China

As a susceptible demographic, elderly individuals are more prone to risks during sudden disasters. With the exacerbation of aging, new challenges arise for urban disaster reduction and prevention. To address this, the key is to establish a community-scale resilience assessment framework based on the aging background and to summarize factors that influence the resilience level of communities. This approach is a crucial step towards seeking urban disaster prevention and reduction from the bottom up, and serves as an important link to enhance the capacity of urban disaster reduction. This paper explores community resilience evaluation indicators under the background of aging, builds a community resilience evaluation index system based on the Pressure–State–Response, uses the entropy weight method to weigh the indicators, and carries out a resilience evaluation of 507 communities in the main urban area of Changchun. The empirical results indicate significant spatial differentiation of community resilience in the main urban area of Changchun. Moreover, the regional development is unbalanced, showing a spatial distribution pattern of weakness in the middle and strength in the periphery. The ring road network highlights the difference between the new and old urban areas. The high contribution indexes of community resilience in the main urban area of Changchun were concentrated on disaster relief materials input, community self-rescue ability, and disaster cognition ability. Finally, strategies to improve community resilience are proposed from the perspectives of stress, state, and response, emphasizing community residents’ participation, conducting disaster prevention and reduction training, and improving community response-ability.

An Optimization Method for Distributing Emergency Materials Which Balances Multiple Decision Criteria

In emergency rescue operations, it is very important for emergency management to arrange emergency materials scientifically and reasonably according to emergency needs. However, the decision criteria for emergency material distribution are often diverse, coupled with the lack of information acquisition due to the suddenness and development complexity of disasters, which makes the scientific decisions about emergency material distribution face great challenges. This paper proposes a multi-criteria decision optimization model of emergency material distribution under uncertainty that combines the 4E criteria of performance evaluation (economic criterion, efficiency criterion, effectiveness criterion and equity criterion). Then, the solution method of the multiple decision criteria model is designed. Finally, a case study of emergency medical material distribution during COVID-19 in China was conducted for model verification. The results show that different decision criteria have an important impact on the distribution of emergency materials, and the proposed model has significant advantages in the allocation of large-scale disaster relief materials, which can provide a useful reference for emergency material distribution under uncertain information conditions.

Research on Solving Postdisaster Material Distribution and Scheduling with Improved NSGA-II Algorithm.

After the occurrence of major sudden disasters, the dispatching and distribution of disaster relief materials are particularly important, but in the process of distribution, there may be excessive distribution of similar emergency materials, unbalanced distribution volume of relief materials in different disaster-affected points, high distribution cost, and low effective distribution rate. In order to solve the above problems, based on the application of big data, this paper proposes a three-level network postdisaster material scheduling and distribution model and an improved NSGA-II algorithm. The model takes the loss degree of the disaster area and the dynamic change rate of the demand for postdisaster relief materials as the constraints, takes the demand prediction of postdisaster relief materials, the optimization of distribution path, distribution nodes, and the satisfaction of victims as the objectives, and designs the sample average approximation method and the improved NSGA-II algorithm. In order to verify the effectiveness of the proposed model and strategy, through the comparative experiment of NSGA and PSO, it can be seen from the experimental results that the three-level network allocation model and the improved NSGA-II algorithm (nondominated sorting genetic algorithm II) proposed in this paper can not only solve the existing postdisaster relief material allocation and scheduling problem but also reduce the space-time complexity of the problem.

A hybrid indicator many‐objective optimization algorithm for the selection and delivery of disaster relief materials problem

AbstractTraditional methods fail to comprehensively consider the selection and delivery of disaster relief materials (SDDM) problem. To solve the problem, the SDDM will be comprehensively considered in this article, which will be built into a many‐objective disaster relief materials selection and delivery model with four objectives to be optimized in the last kilometer of the disaster relief organization. Meanwhile, a many‐objective optimization algorithm is designed to solve the proposed disaster relief materials model by employing the different excellent indicators. Two extensive simulation experiments are carried out. On the one hand, the performance of the designed many‐objective is tested on DTLZ and WFG benchmark functions. On the other hand, the proposed many‐objective model is solved by employing the designed algorithm. In addition, the simulation result shows that the designed algorithm is effective in solving the SDDMs problem.

Extending dynamic capabilities towards lean thinking in humanitarian supply chains

Humanitarian supply chain (HSC) research is still in its infancy and remains an enigma, due to its profound differences with the much-researched field of global supply chains. Thus, humanitarian operations (HO) remain obstinately difficult to manage, despite attempts by key stakeholders to keep abreast of all the contemporary challenges. A key concern is wastage of disaster relief materials along the supply chain, which strains already scarce resources. Moreover, humanitarian research is plagued by a dearth of theory development and redeployment of existing theories from other fields, which are critical in enhancing methodological rigour. To address these gaps, we undertake an in-depth qualitative study which draws on data from humanitarian organisations that responded to the major earthquake in Nepal (2015). Using a novel approach, we adapt the theory of constraints (TOC) and dynamic capabilities to conduct our investigation. First, we apply TOC at an analytical level to unearth the constraints perturbing HO. Second, using dynamic capabilities as an overarching theoretical lens, we draw insights which contribute towards effective HSC management. To conclude, our study contributes by extending the dynamic capabilities theory for Lean thinking in HO. We achieve this by proffering ‘sustaining’ as a key extension of dynamic capabilities in HSC.

Modeling and Simulation of Collaborative Dispatching of Disaster Relief Materials Based on Urgency

In order to address the lack of collaborative decision and failure to notice the emergency and fairness of relief after disasters have occurred, a collaborative decision-making system for emergency relief materials dispatching is established. According to the forecast of the demand for postdisaster relief materials, the entropy weight-TOPSIS method is applied to measure the urgency of the disaster area; then, a “Hub-and-Spoke” dispatching network is constructed. In this paper, a multiobjective collaborative relief material dispatching model is built, which has great performance in terms of minimal distribution cost and maximal fairness, and the objective of fairness requires minimizing the penalty cost caused by unsatisfied demands. Based on the urgency of demand points, the simulated annealing algorithm is designed to solve the Pareto disaggregation of multiobjective optimization model. The performance of the model is verified with the case of Wenchuan Earthquake. The results indicate that if the fair distribution of supplies is emphasized, it will increase the number of rescue vehicles and the number of distribution batches. On the other hand, a variety of relief material dispatching plans can be provided based on calculation of the Pareto front for policy-makers.

Construction of Earthquake Rescue Model Based on Hierarchical Voronoi Diagram

Traditional earthquake rescue methods have many problems, such as the impact of road damage on earthquake rescue, the rational allocation of disaster relief materials, and the active division of rescue areas. According to the characteristics of earthquake relief, a new earthquake rescue model is designed from three aspects: high-altitude rescue, road transport relief supplies, and street human resources rescue. In this paper, the hierarchical Voronoi diagram is applied to the earthquake rescue problem, the earthquake rescue model is constructed, and the area affected by the earthquake is reasonably divided. We discussed the earthquake intensity and the proportion of the population in the disaster area and the number of disaster relief materials and other parameters and conducted an in-depth analysis of the model to form a useful earthquake rescue model. Visual simulation results have been obtained by computer simulation. Compared with the traditional earthquake rescue plan, the model proposed in this paper is more effective and scientific in improving the material distribution, personnel rescue, and postdisaster reconstruction after the earthquake, and it also provides a new idea for the rescue of other natural disasters. It has practical social value and broad application prospects. Besides, the models and conclusions given in this paper have been recognized by the Seismological Bureau of Hainan Province and the Mathematics Research Center of Hainan Province.

Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting

There has been tremendous interest in blockchain technology (BT) (also known as distributed ledger technology) around the globe and across sectors. Following significant success in the financial sector, other sectors, such as humanitarian sector, have started deploying BT at various levels. Although the use of BT in the humanitarian sector is in its infancy, donors and government agencies are increasingly calling for building BT-enabled swift-trust (ST) and more collaborative relationships among various humanitarian actors in order to improve the transparency and traceability of disaster relief materials, information exchanges and flow of funds in disaster relief supply chains. Our study, which is informed by organisational information processing theory and relational view, proposes a theoretical model to understand how BT can influence operational supply chain transparency (OSTC) and ST among actors engaged in disaster relief operations. Our model also shows how BT-enabled ST can further improve collaboration (CO) among actors engaged in disaster relief operations and enhance supply chain resilience (SCR). We formulated and tested six research hypotheses, using data gathered from international non-governmental organisations with the help of the Coordinator for Humanitarian Affairs (OCHA) database. We received 256 usable responses using a pre-tested survey-based instrument designed for key informants. Our results confirm that our six hypotheses were supported. Our study offers significant and valid contributions to the literature on ST, CO and SCR and BT/distributed ledger technology. We have also noted the limitations of our study and have offered future research directions.