Location selection of emergency supplies repositories for emergency logistics management: A variable weighted algorithm

Feng, Jian-Rui; Gai, Wen-mei; Li, Ju-ying; Xu, Ming

doi:10.1016/j.jlp.2019.104032

Cited by 24 publications

(18 citation statements)

References 18 publications

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“…Logistics network, as an essential conveyor of tangible materials between suppliers and receivers, is played a significant role in the emergency relief process and has been widely discussed in most literature (Chang et al, 2007;Feng et al;. In addition to the flow of resources, transportation and information, certain relationships exist among different agents in a rescue network.…”

Section: Literature Reviewmentioning

confidence: 99%

An emergency supplies scheduling for chemical industry park: based on super network theory

Yuan

Wang

2022

Environ Sci Pollut Res

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In a concentrated area of Chemical Industry Parks (CIPs), emergency relief efficiency is not only affected by the rescue capability of themselves, but also their relationships with other CIPs. Academic literature suggests the use of multiple networks such as transport network and information network, in the emergency process after unexpected events, but rarely integrates them ideally in practice. This paper utilizes the super network theory to propose a regional emergency scheduling model to bridge the logistic and relation among CIPs. The proposed super-network model is composed of resources flow network and relationship network that fill a gap of only considering emergency logistic supply chain. Therefore, the main problem is to how coordinate all the disaster relief actors including primary relief centers (PRC) local relief centers (LRC) and CIPs. The proposed model provides an optional answer regarding the optimal configuration (one-stage or two-stage), the optimal type, number and transportation direction of resources. We turn the optimization problem into a variational inequality problem and develop a modified projection algorithm to solve the problem and compare the performance under several disaster scenarios. The practicability of the model is proved by the result of the numerical example given.

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Section: Literature Reviewmentioning

confidence: 99%

An emergency supplies scheduling for chemical industry park: based on super network theory

Yuan

Wang

2022

Environ Sci Pollut Res

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“…The fifth is hysteresis. The initiation of emergency supplies occurs after the emergency event, which already lags behind the event [19]. Developed countries have researched the management of public emergencies earlier.…”

Section: A Emergency Managementmentioning

confidence: 99%

Application of Medical Material Inventory Model Under Deep Learning in Supply Planning of Public Emergency

Huang

Gan²,

Zhi

2021

IEEE Access

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The purposes are to solve inventory management problems in emergencies, optimize inventory management structure, and improve management efficiency. The medical material inventory management is taken as the research object. According to previous research, the existing material management model has problems such as management confusion, resource waste, and insufficient data analysis. Hence, the strengths of deep learning algorithms are utilized to address the above problems. A deep learning-based medical material inventory management model is constructed through the reasonable classification of material management methods. This model effectively utilizes the data by analyzing disaster data in different regions and establishes a corresponding inventory management model according to the classification standards. The numerical analysis of three examples further verifies the effectiveness of the proposed model. On this basis, the model is compared with the latest inventory management models to further determine its advantages. Results suggest that the medical supplies management model based on deep learning can interpret and analyze the data well and calculate the optimal inventory and management method of the model with limited funds based on the data. Compared with the latest inventory management models, the proposed model can provide a prediction accuracy as high as 92.45%. Under the same data, the analysis time of the medical material management method based on deep learning is only 35 minutes, which has undeniable advantages compared with other models. The proposed model can provide research ideas for material management in emergencies.

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“…At present, most studies on emergency management are based on operational researches and related prediction theories to solve the problems of single-objective or multi-objective decision-making, single-factor or multi-factor optimization, and combinatorial optimization. As regards the aspect of using operations research as a tool to solve problems, Zhang [1] proposed that the government and local enterprises should cooperate to reserve materials so as to improve the compliance to the emergency demand and put forward the optimal reserve allocation strategy of local government authorities using the scenario-based integer programming method. Feng et al [2] proposed a mathematical model for emergency material warehouse location by considering practical factors and designed a variable weighting algorithm to solve the model according to the theory and method of solving multiobjective optimization problems in operational research.…”

Section: Literature Reviewmentioning

confidence: 99%

Emergency Supply Control from the Perspectives of Peacetime and Wartime: A System Dynamics Simulation

Zhao

El-Sayed

et al. 2021

Complex Syst. Model. Simul.

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The supply of emergency materials is the fundament of emergency rescues. In view of the demand for emergency materials in major calamities, in this paper, a system dynamics model of emergency materials is constructed from the perspectives of wartime and peacetime. By setting and controlling the relevant parameters and variables, the influence of a variable on the demand and supply of emergency materials and the influence of government strategies on the quantity and provision of emergency material supply are analyzed. We explore the measures that can better ensure the supply to stabilize the social and economic security of the country. The results show that the emergency degree of an event will lead to increases in the amount of government expenditures and in the duration of such expenditures. Meanwhile, the increase in emergency cases will increase the variation range of the supply and demand deviation curve, lengthen the response time to demand, and fasten the growth trend of material supply. The Chinese government adopts comprehensive regulation and control mode, which make the supply and demand reach the equilibrium state more than twice as fast as other control methods. In addition, the promotion of publicity will improve the number of civil materials. A high inflation rate will lead to high imports of government materials, which will consequently affect the supply of emergency materials. The above research findings have important reference significance for the government's emergency materials management.

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Location selection of emergency supplies repositories for emergency logistics management: A variable weighted algorithm

Cited by 24 publications

References 18 publications

An emergency supplies scheduling for chemical industry park: based on super network theory

An emergency supplies scheduling for chemical industry park: based on super network theory

Application of Medical Material Inventory Model Under Deep Learning in Supply Planning of Public Emergency

Emergency Supply Control from the Perspectives of Peacetime and Wartime: A System Dynamics Simulation

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