Research on Emergency Logistics Scheduling Model Based on Disruptions

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.

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.

A burgeoning body of research has examined the influence of personal and contextual features on employee creativity. Disruptive events permeate increasingly dynamic and uncertain business environments. However, little research has examined when and how disruptive events impact employee creativity. Drawing from event system theory and the creativity literature, this study tests a model in which disruptive event characteristics (i.e., event novelty and criticality) and individual differences (i.e., employee learning orientation) jointly foster employees¡¯ improvisational responses and ultimately employees¡¯ creativity. Our findings based on a three-wave onsite survey of employees and supervisors show that in the presence of disruptive events that are critical and novel, learning-goal oriented employees are most likely to engage in improvisation, which in turn leads to employee creativity.

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.

In view of the current problems in China’s logistics industry, such as easy delay of goods distribution information, inconvenient location of express delivery stations for customers, and information level to be improved, the “internet plus Logistics” method is used to improve the efficiency of resource allocation. It can not only effectively play the positive effect of the logistics network, but also achieve the goal of orderly and efficient logistics distribution at lower logistics costs. Therefore, it is very important to discuss the social and economic significance of a logistics management distribution system based on logistics network. Through the organic connection between the central processing unit and each functional module, the system can not only enable customers to obtain corresponding logistics information in real time, but also realize distribution for other customers in the same area under convenient conditions. As a result, the system can not only reduce the number of delivery personnel at logistics terminals, reduce the operating costs of logistics companies and improve the efficiency of logistics distribution in the region, but also provide part-time jobs for the delivery personnel, thus realizing the purpose of rewarding the delivery personnel according to the actual number and weight of the delivery items, increasing personal income and driving the development of the regional economy.

In 2021, economic losses due to supply chain disruptions in the Eurozone amounted to €112.7 billion Euro: Natural catastrophes (e.g., hurricanes, earthquakes, floods, and wildfires) multiply in the wake of climate change. The risks of pandemics, trade restrictions, cyber-attacks, and geopolitical conflicts are omnipresent. Hence, the threat of disruptive events to the European transport network grows ever greater. Additionally, GHG emissions can drastically increase by up to 50% if disruptions are not treated efficiently. Here, the project “Resilient multimodal freight transport network” (ReMuNet) comes into play: ReMuNet will enable the multimodal freight network to react and respond 20% more quickly to disruptive events and help to reduce European inland transport emissions on the main run by over 50% by 2026. As a trailblazer for the Physical Internet, the project pursues the vision to enable and incentivize synchro-modal relay-transport on European rail, road, and inland waterways to increase holistic network resilience. ReMuNet can identify and signal disruptive events and assess their impact on multimodal transport corridors. It reacts quickly to disruptive events in real time. It supports TMS providers to improve route planning resilience by communicating alternative, pre-defined, multimodal transport routes. ReMuNet orchestrates route utilization, suggests transshipment points, and optimizes capacity allocation, minimizing damage and shortening the recovery time. This paper introduces ReMuNet and its vision, objectives, and expected results.

With the frequent occurrence of all kinds of emergencies, the importance of emergency logistics distribution has become increasingly prominent. This thesis focuses on the field of emergency logistics distribution, aiming to analyze distribution models and methods to improve the efficiency and effectiveness of emergency material distribution. First, the characteristics and needs of emergency logistics distribution are analyzed in depth, including time urgency, uncertainty and multi-targeting. Then, for the two key aspects of cost and benefit, cost components such as transportation cost, warehousing cost, labor cost, loss and damage cost, and benefit indicators such as rescue effect, economic benefit and social benefit are elaborated in detail. It also explains that factors such as material response time, transportation speed, completion rate and accuracy should be considered. Meanwhile, in the cost and benefit analysis, methods such as cost-benefit ratio (CBA), cost-efficiency analysis (CEA) and benefit assessment are illustrated, and finally recommendations covering various aspects are put forward to improve the emergency logistics and distribution system.

In recent years, sudden events such as public health events have occurred frequently, which has seriously hindered China's economic development. Reasonable scheduling of emergency supplies can effectively reduce the harm caused by emergencies, and it is of great significance to ensure the production and life of people in disaster areas. In order to ensure that emergency materials can be quickly and efficiently distributed to the affected areas after major emergencies, the vehicle scheduling optimization problem in emergency logistics is studied, that is, to quickly screen the best driving route in a complex road network system to deliver emergency materials to the demand location in the shortest time. In this paper, a model with hard time window is established for emergency logistics vehicle routing optimization problem, and the improved saving algorithm in the shortest path algorithm is selected to solve the emergency material dispatching example in Wuhan area. The experimental results show that the algorithm in this paper has a good effect in solving the problem of emergency supplies scheduling. The algorithm has a good application prospect in reducing the cost of emergency supplies scheduling, shortening the travel time of emergency logistics vehicles and improving the satisfaction of emergency supplies demand points.

Based on the basic concept of digital twinning and virtual reality, this paper constructs the five-dimensional structure model of logistics distribution digital twinning and the overall framework of logistics distribution system driven by digital twinning. At the same time, this paper studies and designs the intelligent scheduling management system and establishes the software system architecture and communication network. The system aims at the problem of simultaneous distribution vehicle routing with random cargo demand under multi-center joint distribution mode. At the same time, the width and depth of adaptive neighborhood search frequency strategy and adaptive inferior solution acceptance mechanism are proposed to balance population evolution. The experimental simulation shows that the system can effectively solve the road disturbance caused by vehicles or vehicles in the distribution process and achieve better logistics distribution.

Disasters that occur in various locations will definitely have impacts on infrastructure damage such as roads, bridges, markets, shopping centers. The perceived disturbances will eventually disrupt logistics distribution (including food) and other basic needs from the point of entering logistics (logistics center) to evacuation sites (victims). In the case of less severe disasters, disturbances can cause logistical delays from producers to consumers. Finally, this can cause price volatility due to the stocks decrease. This study focuses on areas along the two main routes in Aceh: the East and West routes. The object of this study includes all information related to logistic distribution are producers, collectors, traders, wholesalers, consumers, and shipping companies and related local government agencies. This study applied scenario based on the combination of multiple models and geographical information system to identify the optimal location to aid emergency logistics transportation routes. The results of this study indicate that logistics distribution is still very dependent on land transportation modes such as trucks and containers. Ports and airports have not been used optimally while the progress of railway construction is plodding.

In this research we study the berth allocation problem (BAP) in real time as disruptions occur. In practice, the actual arrival times and handling times of the vessels deviate from their expected or estimated values, which can disrupt the original berthing plan and possibly make it infeasible. We consider a given baseline berthing schedule, and solve the BAP on a rolling planning horizon with the objective to minimize the total realized cost of the updated berthing schedule, as the actual arrival and handling time data is revealed in real time. The uncertainty in the data is modeled by making appropriate assumptions about the probability distributions of the uncertain parameters based on past data. We present an optimization-based recovery algorithm based on set partitioning and a smart greedy algorithm to reassign vessels in the event of disruption. Our research problem derives from the real-world issues faced by the Saqr port, Ras Al Khaimah, UAE, where the berthing plans are regularly disrupted owing to a high degree of uncertainty in information. A simulation study is carried out to assess the solution performance and efficiency of the proposed algorithms, in which the baseline schedule is the solution of the deterministic BAP without accounting for any uncertainty. Results indicate that the proposed reactive approaches can significantly reduce the total realized cost of berthing the vessels as compared to the ongoing practice at the port.

A logistics distribution vehicle scheduling model under cloud computing environment is established based on the analysis of factors affecting resource scheduling. The order information and logistics distribution vehicle information processing are completed under the framework of cloud computing, so as to obtain the most reasonable logistics distribution plan. To solve the problem of vehicle allocation in logistics distribution, a distribution path algorithm model and a minimum delivery cost algorithm model are established to provide the best strategy for logistics distribution scheme.

This paper considers the way how supermarket, logistics companies and supplier interact with each other to optimize their benefits during the benefits distribution in cold chain distribution process. The quality of cold chain distribution depends on distribution methods, quality level and the accurate controls during distribution process; this requires qualified specialized logistics companies to fulfill. Due to the strict requirement and high cost of cold chain distribution, its participants are willing to form a cooperative entirety to make more benefit. The benefits distribution in turn affects the overall benefit in the cold chain food logistics. Therefore, we need research benefits distribution in the cold chain food logistics under different conditions. The problem is formulated as a Stackelberg game with two sub-games. One is the alliance of logistics companies and supermarket and the other is the alliance of logistics companies and supplier. We analysis in-depth benefits distribution of different parts as well as the entire supply chain under different circumstances by discussing the distribution of benefits among supermarket, supplier and logistics companies. A numerical example is conducted to test the proposed model and algorithm, and gain managerial implications.

Monitoring the hatch process demands continuous assessment of the number of hatched chicks, which is usually a disruptive event as it requires the incubator door to be opened. Therefore, a real-time monitor for the hatching time of individual chicks is of interest to both researchers and industry. An alternative non-invasive method which involves measuring the eggshell temperature using small, accurate temperature sensors is presented. Continuous recordings of eggshell temperature (Tegg) of the focal eggs were analysed and the temperature profiles for plotted Tegg showed a temperature drop of around 2-6 °C when the chick hatched. It was therefore possible to identify the hatching time for individual eggs in real time during incubation based on this registered temperature drop. Furthermore, linear regression analysis showed a positive correlation between hatching time (r=0.32; P=0.001) and chick weight at take-off which indicated that early hatched chicks started to lose weight during the holding period.

This study aims to improve the efficiency of logistics distribution scheduling in the supply chain and reduce logistics costs. In the current research, the time and cost problems of logistics distribution always have some limitations to meet the needs of practical applications; therefore, this paper designed genetic algorithm-based method to solve the vehicle scheduling problem. The analysis of arithmetic examples was carried out. The analysis found that the method effectively reduced the cost of distribution and had higher computing speed, showing a high performance in solving the problem of logistics distribution scheduling. The method can further optimize the logistics distribution of the supply chain. This work provides a new approach for the study of logistics distribution scheduling model and is conducive to the better application of genetic algorithm in this field.