Research on Emergency Logistics Vehicle Route Scheduling and Optimization Method Based on Multi-Intelligent Decision System

Aiming at the problems of complex urban road network, low efficiency of logistics distribution, and the difficulty of large-scale logistics distribution area division and routing planning, this paper proposes a two-stage logistics distribution vehicle routing optimization (VRP) method based on the establishment of a multi-factor complex road network constrained logistics distribution mathematical model. Considering the complex traffic elements and road network topological structure in logistics and distribution, in the first stage, a heuristic simulated annealing (HSA) distribution region partitioning algorithm is proposed with the objective of balancing vehicle task load to divide the urban logistics distribution network under complex road networks, so as to reduce the area scale and path search cost. In the second stage of route decision making, aiming at minimizing the total cost of logistics distribution, combining the VRP problem with complex road network conditions, a heuristic path search method combined with complex road network model constraints is proposed. In this stage, a hybrid genetic beam search(HGBS) algorithm is used to plan the path nodes, reduce the randomness of the model in the initial search for paths by heuristic genetic algorithms, then combine with Beam graph search methods to reduce the space and time used for the search, and use optimization algorithms to improve the accuracy of independent sub-region routing optimization and the rationality of overall physical distribution route selection. Finally, the proposed method is validated in this paper with two practical cases. The experimental results show that the two-stage decision-making algorithm proposed in this paper has certain advantages in partitioning schemes, minimizing total cost and iteration times. Through comparison, the optimization ability of this method for logistics distribution networks is proved.

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.

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.

In recent years various disasters with enormous consequences occurred frequently around the world. Emergency Logistics, a new field of logistics which plays a key role in disaster relief and aftermath recovery, has got much attention and become a new efficient methodology in dealing with disastrous consequences. This paper illustrates the theory, practice development, specific characteristics and concept of Emergency Logistics. For emergency logistics management, the most important part is the establishment of emergency logistics system. Enlightened by the present theory and results, an Operations Reference Model for Emergency Logistics System is proposed, in which the support mechanism, compositional elements and functionalities of Emergency Logistics System are discussed in this essay. It is necessary that it has potential value for further study or practical use of Emergency Logistics Management.

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.

Emergency logistics refers to the transportation, storage, and distribution of materials to ensure the safety of people’s lives and property and social stability in an emergency or disaster. Since the outbreak of COVID-19, the state and society have paid more attention to constructing emergency logistics systems. In recent years, the research on route optimization and location selection of emergency logistics has also increased. The study of emergency logistics location and routing is significant for improving emergency logistics efficiency, optimizing resource allocation, improving emergency response capabilities, and reducing emergency risks. It can provide scientific decision-making support for emergency management departments and logistics enterprises, promote social emergency management level improvement, and ensure the safety of people’s lives and property. This article studies relevant literature on domestic and international emergency logistics routing and location issues in recent years, summarizes the main models and related algorithms to solve this problem, analyzes the current research status in recent years, and looks forward to future research directions.

In recent years, there have been frequent public health emergencies that have brought great harm to people's lives. Among them, major infectious diseases spread rapidly once they break out. They are characterized by a wide range of infections, rapid spread, high degree of mutation and lasting harm, and difficulty in initial control. Based on this, the focus and research on emergency logistics are gradually carried out. Based on previous literatures on emergency logistics, this paper reviews literatures on three research hotspots of emergency logistics, multi-objective optimization, and vehicle routing of emergency materials, hoping to provide some help for future in-depth studies on emergency logistics.

Aiming at the problems of low efficiency and slow iteration convergence of existing distribution vehicle routing optimisation algorithms, a logistics distribution vehicle routing optimisation algorithm based on cloud model is proposed. Data are trained and learned using the deep belief network (DBN) model. According to label data and model training results set manually, the road condition of logistics distribution route is predicted. Combined with genetic algorithm and cloud model theory, the real-time solution and update of time-sharing weights of time-sharing weighted network paths are realised, and the global optimal solution is obtained. The experimental results show that compared with the existing algorithms, the logistics distribution time of the research algorithm varies in the range of 70 s-37 s, and the efficiency of logistics distribution is high. When the number of iterations is 1,000, the path length of this algorithm is 2,400 km, and the iteration convergence is fast.

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 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.

Long duration, to-and-fro interleaving transportation among multi supply places and multi demand places are main features of emergency goods logistics under large scale emergency incidents. To implement large scale emergency goods distribution effectively according to demand, the routes logistics optimization model among multi supply places and multi demand places under large scale emergency incident is established. Several preconditions of the model are given, the optimization objectives include that emergency routes should be selected along the largest emergency goods flow direction, the curve degree of emergency routes should be minimized, the burden of emergency routes should be balance, and the repeat parameter of emergency network should be minimized as far as possible. Some constraints such as transportation quantity, length, curve degree of emergency routes, avoiding of isolated point and the number limit of emergency routes are considered. Above multi-objective non-linear programming model is transferred, and its solving method by GA is designed. The emergency logistics problem within one certain typical region is taken as the research instance, the validity of the model and its solving algorithm is validated. The obtained calculation result shows that, under the precondition of meeting the emergency routes' length and flow quantity, the emergency network performances such as repeat parameter, route exchanging times per transportation, number of isolated nodes, burden balance degree of emergency routes, average curve degree of emergency routes are satisfied. Under large emergency incidents, above routes optimization model and algorithm will benefit for improving efficiency and precision of emergency logistics, and its maneuverability is strong.

From the views of emergency logistics scheduling, the disruption events during the process of logistics distribution are discussed and classified into three groups by its impacts on the status of goods, vehicles and roads, also the characteristics of the disruption events are examined. An object-oriented modeling frame of emergency logistics scheduling based on disruptions is put forward in this paper. The model frame is composed of four sections, the static section, the dynamic section, the function section and the model repository section. The static section consists of the objects, the attributes and the operations of the objects. The dynamic section consists of the goals, the restrictions of the system and the operating process of the dynamic section. The function section consists of the identifying of the status of the objects and the logic judgments, which can be used to control the operating process of the model. The model repository section gathers the relevant logistics algorithms classified to the demand of emergency logistic rescheduling under disruptions in order that the effective logistics algorithms or their combination can be obtained quickly and accurately when a disruption event occurs. The method proposed in this paper will supply a new perspective for the research of theory and decision support application in the disposal of disruptions and real time controlling during logistics distribution.

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.

The main purpose of this study is to verify whether previous low level of labor costs being one of competitive edges of CEE countries is a factor that may determine competitiveness of this region in the long run. In the study a regression analysis has been carried out on the sample of all EU countries in order to verify the dependence between internationalization degree measured by OFDI stock per capita on labor costs in manufacturing sector and on GNP per capita. The results of the regression analysis clearly show the occurrence of such dependence. This means that gradual increase in labor costs in CEE countries will result in not only reduced inflow of investments from developed countries to this region but also transfer of production to more cost competitive countries. In order to exemplify the above econometric model I carried out empirical analysis of the companies listed on the Warsaw Stock Exchange, identifying the companies for which efficiency-seeking is the main internationalization motive. The analysis of internationalization of 26 companies during the years 1990-2010 clearly shows that a significant part of investments is located outside the territory of Poland, in the countries with lower labor costs. This fact confirms that CEE countries will gradually become less and less attractive in terms of costs not only for MNEs from developed countries but also for the companies originating from transition economies.