Emergency logistics management and its operations reference model

The infectious disease COVID-19 has swept across the world in 2020, and it continues to cause massive losses of life and severe economic problems in all countries. Providing emergency supplies such as protective medical equipment and materials required to secure people’s livelihood is thus currently prioritized by governments. Establishing a reliable emergency logistics system is critical in this regard. This paper used the Delphi method to design a formal decision structure to assess emergency logistics system reliability (ELSR) by obtaining a consensus from a panel of experts. Assessing ELSR is a typical multiple-attribute decision making (MADM) problem, and the related MADM methods are usually on the basis of symmetry principles. A hybrid MADM model, called the Decision Making Trial and Evaluation Laboratory (DEMATEL)-based Analytical Network Process (D-ANP), was developed to identify the critical factors influencing ELSR. An analysis of empirical evidence showed that the emergency logistics command and coordination system and the emergency material supply system play important roles in ELSR, while the emergency logistics transportation and distribution system and the emergency information system are not so important. This conclusion is different from previous research about traditional disaster emergency logistics. Moreover, the cause–effect relationships among the key factors indicated that the system of command and coordination for emergency logistics and the supply system for emergency materials should be improved. Accordingly, effective suggestions for emergency logistics services for epidemic prevention are provided in this paper. The main contributions of this paper are (1) establishing a comprehensive and systematic evaluating index of ELSR for epidemic prevention; (2) employing a kind of structured, namely D-ANP, to identify the critical factors with non-commensurable and conflicting (competing) characteristics; and (3) comparing the differences of reliable criteria between the emergency logistics of epidemic prevention and the traditional disaster emergency logistics.

Due to the sudden disasters have occurred frequently, unpredictable, impact and characteristics of growing, in order to do better Management of disaster prevention and mitigation, it should from the strategic level to build an efficient emergency logistics system. In this paper, research progress at home and abroad, through the analysis of emergency logistics system, Sichuan development present situation and main problems of emergency logistics system, targeted the proposed hierarchical management mechanism of emergency logistics management system, establish a coordination mechanism of the government and social resources, break through the emergency logistics management system of technical methods and strengthening the construction of disaster emergency logistics risk early warning management system in our province, so as to promote the development of emergency logistics management system in Sichuan province.

Emergency logistics management has emerged as a significant global concern in the wake of numerous global disasters over the past few decades. While these crises have undoubtedly enhanced humanitarian assistance in the realm of relief supply and distribution, the necessity for effective and efficient emergency logistics management persists throughout and beyond the disaster cycle. It is therefore of paramount importance to ensure the existence of an effective emergency logistics management system to address potential contingencies. In this paper, we utilized AnyLogic to simulate a geographic information system (GIS)-based distribution model, which considered 3 warehouses, and 15 outlets. In this model, key parameters are considered, including carbon emissions, mileage, and energy consumption, to determine the optimal time to handle materials and the most efficient routes for delivery. The simulation results can provide insights for more effective material distribution in future emergency situations. For instance, route optimization can reduce total operational costs, emphasizing the importance of routing optimization. Inventory costs represent a significant portion of total costs, and therefore, optimizing inventory management is crucial to tradeoff cost and efficiency. Moreover, incorporating real-time data analytics into the model can further enhance decision-making by predicting demand fluctuations and adjusting routes dynamically. This approach not only ensures timely deliveries but also minimizes the carbon footprint and overall environmental impact of emergency logistics operations, making the entire process more sustainable.

Increasing disasters in recent years have necessitated the development of emergency logistics plans. Evacuation planning plays an important role in emergency logistics management, particularly when it comes to addressing transit-dependent populations that are often neglected in previous studies. This systematic literature review explores the current state of transit-based evacuation planning and examines the current gaps. We focused on transit-based evacuation planning problems that used optimisation and modelling approaches. This review conducts an extensive analysis of relevant studies to provide a comprehensive overview, identify research gaps, and outline future directions in the evacuation planning body of knowledge. Using an integrated systematic review methodology, a thorough search of the Scopus and Web of Science databases was conducted, resulting in a total of 538 articles. These articles were screened and evaluated based on predetermined inclusion and exclusion criteria, ultimately yielding 82 studies for final analysis. The findings highlight the growing importance of optimisation and modelling approaches within transit-based evacuation planning. Studies emphasize the integration of public transportation networks into evacuation strategies to enhance operational efficiency, optimize resource allocation, and ensure evacuee safety. Transit-based evacuation planning is vital for both those without personal vehicles, making evacuation more equitable, and vehicle owners, particularly in earthquakes where vehicles might be inaccessible or trapped, demonstrating its wide usefulness in all emergency scenarios. Various optimisation and modelling approaches have been employed in transit-based evacuation planning studies to simulate and analyse the flow of evacuees and vehicles during emergencies. Transit-based evacuation planning exhibits unique characteristics within disaster management, including the consideration of spatial and temporal dynamics of transit systems, integration of social and demographic factors, and involvement of multiple stakeholders. Spatial and temporal dynamics encompass transportation schedules, capacities, and routes, while social and demographic factors involve variables such as income, age, and mobility status. Stakeholder engagement facilitates collaborative decision-making and effective plan development. However, transit-based evacuation planning faces challenges that require further research and development. Data availability and accuracy, model validation, stakeholder coordination, and the integration of uncertainty and dynamic factors pose significant hurdles. Addressing these challenges necessitates advances in data collection, robust modelling frameworks, and improved communication and coordination mechanisms among stakeholders. Addressing these gaps requires interdisciplinary collaborations and advances in data analytics and modelling techniques.

The marine economy has become a growth point for the regional economy. International resource exchange is mainly achieved through marine transportation. Ports play a vital role in marine transportation and also play an important role in some large-scale international rescue activities. When an emergency occurs in the port, the port emergency logistics system has an important impact on the collection and distribution of materials, which can effectively reduce the negative impact and economic loss caused by the emergency. Through in-depth analysis of the emergency logistics system, design the comprehensive evaluation system of the port emergency logistics distribution system, and based on the characteristics of the grey, fuzzy and difficult to quantify the influencing factors of the emergency logistics distribution system, apply the analytic hierarchy process and grey system theory to establish the gray level comprehensive evaluation model of the port emergency logistics distribution system. In this model, the analytic hierarchy process is used to determine the index weight, and then the grey theory is used to comprehensively evaluate the emergency logistics distribution system. Finally, the port is used as a case to verify the practicability and effectiveness of the model.

With the frequent occurrence of global emergencies, emergency management under disaster is facing great challenges. As an important rescue support measurement, the emergency logistics system (ELS) faces vulnerability problems due to the interference of external factors and instability of the internal factors. In order to solve the problem of vulnerability of ELS, this paper builds a comprehensive vulnerability evaluation index system of emergency logistics system on the basis of DPSIR model (Driving force, Pressure, State, Impact and Response). While this paper proposes a vulnerability evaluation model of ELS based on Fuzzy Matter-Element Method, and conducts a case study to verify the feasibility with the data of Shaanxi Province from 2010 to 2019. The empirical results show that the vulnerability of the emergency logistics system in Shaanxi Province is decreasing year by year, which indicates that the responsive capability of the ELS in Shaanxi Province is gradually improving. The study provides a new insight to estimate the vulnerability of emergency logistics and increase the responsive capacity of the system. Keywords-vulnerability; emergency logistics system; DPSIR model; fuzzy matter-element model

Efficient solution algorithms for a time-critical reliable transportation problem in multigraph networks with FIFO property

Logistics distribution vehicle planning is an important issue in logistics transportation activities, and it is also a research hotspot in theoretical circles at home and abroad. At present, many studies have focused on establishing vehicle planning models and optimizing vehicle planning in different environments and have achieved rich results. As an important part of transportation production process, the efficiency of logistics distribution is very important to the whole production process. Especially for emergency logistics, every minute is very critical for emergency situations such as disaster relief. In order to improve the efficiency of emergency logistics, this paper applies multiagent technology to emergency logistics and puts forward an integrated modeling method of enterprise macromodeling, business process mesomodeling, and micromodel design. Using the agent-oriented system development method, an emergency logistics distribution vehicle planning model system is established. The development process of multiagent automatic trading system is described. The results show that it is feasible and effective to use multi-intelligent fuselage technology for emergency logistics distribution vehicle planning and decision-making. The algorithm proposed in this paper has advantages over the container order sequence processing scheme, and the total cost of order acceptance decreases sharply in the initial stage, which shows the practical convergence of the algorithm. The adjacency search method and Tabu search method deal with the calculation of total labor cost, and the Tabu neighborhood search algorithm obtains better results with lower labor cost.

Purpose - This study, against the backdrop of the city of Wuhan, China, where COVID-19 first appeared, examines the factors that affect the effectiveness and efficiency of emergency logistics through empirical research on relief organizations that support Wuhan, China, during the fight against COVID-19. This study also studies how the government’s control situation affects the effectiveness and efficiency of emergency logistics. Design/Methodology/Approach - We employed a quantitative research method using survey data collected in Wuhan, China. This paper tested five hypotheses which assumes the effect of transportation system, inter-organizational cooperation, emergency logistics center location and demand and inventory management on the emergency logistics performance. In addition, we also examined a moderating role of government control on those hypothesized relationships. Findings - We found that transportation system, inter-organizational cooperation, emergency logistics center location and demand and inventory management affected the emergency logisitcs performance positively, and government control have moderated those reloationships partially. Research Implications - This findings may give meaningful insights on successful management of emergency logistics in Korea.

In this article, in order to optimize emergency logistics system for post-earthquake, a stochastic dynamic LRP model on relief distribution centers was developed by considering dynamic characteristics of emergency logistics networks in post-earthquake. According to the characteristics of the model, the paper proposes an improved genetic algorithm based on dynamic programming. The authors adopt a special real-valued coding scheme and a punished function method to deal with restriction in the model. The results of a numerical example show that the proposed model and algorithm can resolve relief distribution centers location-allocation and vehicle routing problem in post-earthquake emergency logistics systems efficiently, and it can help the government agencies provide assistance in decision-making.

In recent years the earthquake happens frequently, China is one of the countries that suffer the most. The earthquake caused great harm to the national economy and the social development. Under this circumstance, it’s necessary to have the research of route optimization in the earthquake.Through the analysis of the actual situation of earthquake disasters, this paper expounds the earthquake disaster emergency logistics of road transportation route choice effects, such as distribution lines, total delivery time, traffic volume, road traffic capacity and its safety factors influencing decision-making, and points out the goal that the earthquake disaster emergency logistics management needs to achieve. Then, the introduction of the minimum time and the maximum flow theory constructs the based model and determining the seismic disaster emergency logistics system highway transportation route choice the basic train of thought to clear the path and freight volume constraint conditions each other, established the earthquake disaster emergency logistics system highway transportation route choice model, and puts forward some solutions to this model algorithm. Finally, through an example, the paper validates the feasibility of the model and the algorithm. Keyword-Earthquake disaster; Emergency logistics; Road transportation; Route optimization

Stochastic network models for logistics planning in disaster relief

This study focuses on collaborative UAV/UGV routing problem in emergency logistics aiming to optimize the coordinated delivery efforts of both vehicles during disaster situations. By using a mixed integer model the study identifies the best delivery points and assigns specific drones to transport medical supplies to designated emergency assembly points. The research methodically assesses how UAV speed, UGV stops and cluster numbers affect delivery time. The results show that increasing UAV speeds and reducing stops and clusters generally lead to deliveries but achieving the time requires a careful balance due to their complex interactions. The study suggests that strategic coordination between UAVs and UGVs can significantly improve the efficiency of emergency logistics systems potentially reducing response times in disaster relief and medical supply deliveries. In conclusion the model highlights the potential for enhancements, in emergency response capabilities that could help save lives and lessen disaster impacts. Future studies should consider adapting the model for conditions and unpredictable scenarios to ensure resilience against demands.

In the modern security system, material support in emergency is an important part. In order to ensure the supply of necessary living materials and proprietary materials in wartime, major natural disasters and emergency epidemics, all countries have introduced corresponding measures. Emergency logistics system is a necessary condition to ensure the smooth and timely distribution of emergency supplies. This paper applies the complex network theory to study the main statistical characteristics of the three-layer emergency logistics system considering the material needs, material manufacturer and raw material resource supplier, which can provide a reference for optimizing the resource allocation and anti destruction ability of the emergency logistics system.

Fuzzy Entropy Clustering Approach to Evaluate the Reliability of Emergency Logistics System