ABSTRACT
Predicting the evolution of the Covid-19 pandemic during its early phases was relatively easy as its dynamics were governed by few influencing factors that included a single dominant virus variant and the demographic characteristics of a given area. Several models based on a wide variety of techniques were developed for this purpose. Their prediction accuracy started deteriorating as the number of influencing factors and their interrelationships grew over time. With the pandemic evolving in a highly heterogeneous way across individual countries, states, and even individual cities, there emerged a need for a contextual and fine-grained understanding of the pandemic to come up with effective means of pandemic control. This paper presents a fine-grained model for predicting and controlling Covid-19 in a large city. Our approach borrows ideas from complex adaptive system-of-systems paradigm and adopts a concept of agent as the core modeling ion. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Open economy, globalization and effect of Covid19 pandemic are transforming the consumer behavior rapidly. The business is nudging consumers towards hyper consumption through online shopping, e-commerce and other conveniences with affordable cost. The companies from courier, express and parcel (CEP) industry are trying to capitalize on this opportunity by tying up with business to consumers (B2C) companies with a promise of delivering parcels to the doorstep in an ever-shrinking time window. In this endeavor, the conventional optimization-based planning approach to manage the fixed parcel payload is turning out to be inadequate. The CEP companies need to quickly adapt to the situation more frequently so as to be efficient and resilient in this growing demand situation. We propose an agent-based digital twin of the sorting terminal, a key processing element of parcel delivery operation, as an experimentation aid to: (i) explore and arrive at the right configuration of the existing sorting terminal infrastructure, (ii) be prepared for possible outlier conditions, and (iii) identify plausible solutions for mitigating the outlier conditions in an evidence-backed manner. This paper presents digital twin of the sorting terminal and demonstrates its use as “in silico” experimentation aid for domain experts to support evidence-backed decision-making. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
In the Post-COVID-19 Era, with the continuous improvement of the technical level, virtual teams are constantly evolving, and the relationship between leadership and the construction of virtual teams has received more and more attention. It is of great significance to explore the influence of participatory leadership on the construction of virtual teams from a psychological perspective by building a multi-agent simulation model. Based on a simulation platform of NetLogo, the results showed that (1) Participatory leadership is conducive to the expansion of the scale of virtual teams by providing greater space for the development of the members of virtual teams and meeting the team members' requirements of planning and promotion in the environment, which is decentralized and non-authoritative. (2) However, losing management is not conducive to building a reasonable structure of team members under participatory leadership. (3) The scale of virtual teams and the efficiency of the virtual teams all depend on the relationship between participatory leadership, organizational trust, incentive mode, and the balance between cooperation and competition.
ABSTRACT
The Corona Virus Disease 2019 (COVID-19) epidemic is a sudden public health crisis, known as an "International Emergency of Public Health Event". This study uses the bottom-up characteristics of multi-agents to construct multi-agent simulation models for COVID-19 prevention and control. The development trend of the epidemic situation under the condition that the government adopts different prevention and control measures is studied, and on this basis, the influence of temperature on the spread of the virus is discussed. The simulation results show that the multi-agent modeling method can effectively capture the emergence of complex systems. The evaluation of the effects of single measures and multiple interventions will help determine key prevention and control strategies and provide important experience and scientific basis for future epidemic prevention and control. © 2022 IEEE.
ABSTRACT
Today, and due to the population growth, the healthcare field recognizes many difficulties and challenges in many countries, especially in the underdeveloped ones. The spread of COVID-19 has shown these difficulties such as the lack of equipment and the failing of patient admission process. Therefore, healthcare systems require quick, newer and more sophisticated solutions that match the speed of technology and the citizens' aspirations. In this context, we propose in this paper a model for improving and helping hospital managers to orchestrate the patient admission process. The proposed model deals with the hospital bed management in order to ensure a quick patient transfer to the nearest and the most appropriate hospital. The proposed model is based on the coupling of multi-agent an edge computing system. Multi-agent systems represent a powerful choice to develop complex, distributed, dynamic and interactive systems, which represent typically our case. In addition, edge computing ensures a real-time collection of data about the bed's availability in the neighboring hospitals in order to transfer the patient to the adequate one as quickly as possible. © 2021 IEEE.
ABSTRACT
Throughout the history of humanity, large-scale epidemics and pandemics have repeatedly erupted. Athenian ulcer, several plague and cholera pandemics, Spanish flu, Avian influenza, Swine influenza, HIV/AIDS-millions of people have died due to lack of medicines and medical knowledge. In the 21st century, it would seem that world medicine is ready and capable of preventing many diseases, but by the beginning of 2020, a new pandemic of the coronavirus disease COVID-19 caused by the SARS-CoV-2 virus broke out. The paper provided a brief systematic overview of modeling methods in epidemiology. A modified SEIRD simulation model of epidemic spread is presented. The proposed model was implemented in the AnyLogic system. © 2021 IEEE.
ABSTRACT
Since December 2019, a new type of coronavirus pneumonia has occurred in Wuhan, Hubei. The strong spread ability of the new coronavirus has led to the rapidly emergence of new coronaviruses throughout the country and even all over the world. In order to portray the spread line of the new coronavirus within the city and then provide reasonable suggestions for the prevention and control of the urban epidemic, this article constructs a new coronavirus intelligent simulation model by combining complex network theory and GIS technology based on the behavior and social relationships of individuals in the city. Considering to the facts that it is necessary to strictly prevent the import of overseas cases to prevent the local epidemic from rebounding in cities with complex composition of population. This agent model takes the first entry point for overseas entry, Guangzhou city, as the research object to review the development of the epidemic. The attributes and rules of the model was determined by collecting statistical data from the literatures. Then the parameters were fitted by the Markov chain Monte Carlo method to achieve an accurate review of the epidemic situation in Guangzhou. The model is of high accuracy whose MAPE value have achieved 0.17. Meanwhile, this model also has good applicability which can simulate the impact of imported cases from abroad on the development of urban epidemics. Since the agent model marks the individual's time and space location and social relationship, this paper proposes a method for epidemiological investigation through the agent model, which is more convenient and more efficient than traditional epidemiological investigations.This article also visually displays the results of the infection chain, which is convenient for analyzing the activity trajectory of virus carriers and close contacts. This model provides valuable decision-making information for urban epidemic prevention and control. Moreover, the simulation results show that if there is another epidemic outbreak in the city, the epidemic will be controlled within 14-20 days so the citizens don't need to be panic. However, it is still necessary to improve self-protection awareness and protect individuals finely, especially the children and the elderly. When the epidemic comes again, it is recommended that schools and enterprises should establish a joint health monitoring mechanism to strengthen the health monitoring of children and employees, respectively. Relevant governmental departments have to strengthened the spread of epidemic prevention knowledge and persuaded retired people to reduce gatherings and wear masks reasonably. 2021, Science Press. All right reserved.