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Evaluating innovation ecosystem resiliency using agent-based modeling and systems dynamics

Journal of Safety Science and Resilience 2024年第2期5卷 204-221页

作者： Soheila Abdi Mehdi Yazdani Esmaeil Najafi Department of Industrial Engineering Science and Research BranchIslamic Azad UniversityTehranIran Department of Industrial Engineering Qazvin BranchIslamic Azad UniversityQazvinIran

Evaluating the resilience of the innovation ecosystem to maintain its performance,in the sense of resistance to disruption and recovery after it,has recently received more attention.Several studies have been conducted to model different ecosystems and evaluate their resilience.However,modeling the innovation ecosystem from a holistic perspective and performing a quantitative assessment of its resilience have received less attention.This paper models the innovation ecosystem holistically and evaluates its resilience index using a quantitative approach through five main steps.In the first step,a case study related to the innovation ecosystem of Iran's Ministry of Energy,called the Power Innovation Ecosystem,is modeled by combining system dynamics and agent-based modeling.Upon validating the model in the second step,the disruption of the loss of experts is investigated in the third step,and all possible actions to recover each actor are analyzed.In the fourth step,the performance of the ecosystem is simulated before and after the disruption using the data gathered in the previous steps.Finally,resilience is calculated in two different ways in the fifth step.Several improvement solutions are also suggested when considering that the resilience index of the innovation ecosystem is at a medium level.This research may assist policymakers in observing the resilience level of the innovation ecosystem based on the proposed model.By applying strategic changes to this model,they can determine the effects of their policies and make the most appropriate decisions to increase the resilience of the innovation ecosystem.

关键词： Resilience index innovation ecosystem System dynamics agent-based modeling

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Adaptive pandemic management strategies for construction sites:An agent-based modeling approach

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Frontiers of Engineering Management 2024年第2期11卷 288-310页

作者： Chengqian LI Qi FANG Ke CHEN Zhikang BAO Zehao JIANG Wenli LIU School of Civil Engineering Hunan UniversityChangsha 410082China School of Civil Engineering Central South UniversityChangsha 410004China School of Civil and Hydraulic Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Energy GeoscienceInfrastructureand SocietyHeriot-Watt UniversityEdinburghUK

In the face of sudden pandemics,it becomes crucial for project managers to quickly adapt and make informed decisions that anticipate the consequences of their actions.This highlights the need for proactive management strategies to enhance epidemic response efforts.However,current research mainly emphasizes the negative impacts of pandemics,often neglecting the development of adaptable management approaches for construction sites.This study aims to fill this research void by developing strategies tailored to managing pandemics at construction sites.Using agent-based modeling,the study simulates the movement patterns of workers and the consequent spread of an epidemic under different risk scenarios and management tactics.The results indicate that measures such as wearing masks,managing group activities,and enforcing entry controls can significantly reduce epidemic spread on construction sites,with entry controls showing the greatest effectiveness.

关键词： epidemic transmission agent-based modeling safety management management strategy

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agent-based modeling of COVID-19 outbreaks for New York state and UK:Parameter identification algorithm

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Infectious Disease Modelling 2022年第1期7卷 30-44页

作者： Olga Krivorotko Mariia Sosnovskaia Ivan Vashchenko Cliff Kerr Daniel Lesnic Institute of Computational Mathematics and Mathematical Geophysics Siberian Branch of the Russian Academy of Sciences 6 Prospect Akademika Lavrentieva StreetNovosibirsk630090Russia Novosibirsk State University 2 Pirogova StreetNovosibirsk630090Russia Institute for Disease modeling Bill&Melinda Gates FoundationSeattleUSA University of Leeds LS29JTUK

This paper uses Covasim,an agent-based model(ABM)of COVID-19,to evaluate and scenarios of epidemic spread in New York State(USA)and the UK.Epidemiological parameters such as contagiousness(virus transmission rate),initial number of infected people,and probability of being tested depend on the region's demographic and geographical features,the containment measures introduced;they are calibrated to data about COVID-19 spread in the region of interest.At the first stage of our study,epidemiological data(numbers of people tested,diagnoses,critical cases,hospitalizations,and deaths)for each of the mentioned regions were analyzed.The data were characterized in terms of seasonality,stationarity,and dependency spaces,and were extrapolated using machine learning techniques to specify unknown epidemiological parameters of the model.At the second stage,the Optuna optimizer based on the tree Parzen estimation method for objective function minimization was applied to determine the model's unknown parameters.The model was validated with the historical data of 2020.The modeled results of COVID-19 spread in New York State and the UK have demonstrated that if the level of testing and containment measures is preserved,the number of positive cases in New York State remain the same during March of 2021,while in the UK it will reduce.

关键词： Epidemiology agent-based modeling COVID-19 Interventions analysis Coronavirus data analysis Forecasting scenarios Reproduction number Optimization Parameter identification

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agent-based modeling approach for evaluating underground logistics system benefits and long-term development in megacities

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Journal of Management Science and Engineering 2022年第2期7卷 266-286页

作者： Wanjie Hu Jianjun Dong Jingfeng Yuan Rui Ren ZHIlong Chen Helan Cheng College of Architecture and Civil Engineering Beijing University of TechnologyBeijing100124China College of Civil Engineering Nanjing Tech UniversityNanjing211800China Department of Construction Management and Real Estate Southeast UniversityNanjing210096China College of Defense Engineering Army Engineering University of PLANanjing210001China Nanjing KENTOP Civil Engineering CO. LTDNanjing210041China

Mobility,pollution,and other barriers against sustainable goods movement are pushing local administrators to seek innovations in urban transportation infrastructure.The urban underground logistics system(ULS)has been recognized as a prospective alternative to realize large-scale automated freight distribution within and around megacities.This paper proposes an integrated approach combing system dynamics and agent-based modeling to evaluate the long-term development and operating status of a city-wide ULS project.The project boundaries regarding underground network expansion,stakeholders’attributes,and social-environmental benefit metrics were structured as eight highly-interacted agent modules.Critical decision variables of agents in terms of supply-demand equilibrium,investment plan,pricing-to-market and willingness-to-pay were incorporated into three formulized subsystem models.From empirical perspective,the urban territory of Beijing,China,was taken as a case to simulate the development footprints of ULS project under different funding options and market acceptance degrees.Results show that ULS has significant competence with respect to service capacity and profitability,while enabling billions of dollars of external cost-saving annually.Moreover,the comprehensive performance of ULS project regarding economic incomes,benefits,market demand,and construction schedule can reach satisfactory trade-offs through adaptively adjusting the funding policies,incentives and pricing portfolios during project development.

关键词： Underground logistics system Sustainabletransport Project development Cost-and-benefit System dynamics agent-based modeling

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Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1022-1038页

作者： Xiao Xue Deyu Zhou Xiangning Yu Gang Wang Juanjuan Li Xia Xie Lizhen Cui Fei-Yue Wang the School of Computer Software College of Intelligence and ComputingTianjin UniversityTianjin 300350China the School of Software and the Joint SDUNTU Centre for Artificial Intelligence Research(C-FAIR) Shandong UniversityJinan 250101China the Information School Xi’an University of Financial and EconomicsXi’an 710100China the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Hainan University Haikou 570228China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 1001901China

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

关键词： agent-based modeling computational experiments cyber-physical-social systems(CPSS) generative deduction generative experiments meta model

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Recent progress in econophysics： Chaos, leverage, and business cycles as revealed by agent-based modeling and human experiments

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Frontiers of physics 2017年第6期12卷 139-161页

作者： Chen Xin Ji-Ping Huang Department of Physics and State Key Laboratory of Surface Physics Fudan University Shanghai 200433 China

agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics. agent-based modeling has been in development for over 20 years, but how to design virtual agents with high levels of human-like ＂intelligence＂ remains a challenge. On the other hand, experimental econophysics is an emerging field; however, there is a lack of experience and paradigms related to the field. Here, we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos, leverage, and business cycles. We also review the principles behind assessments of agents＇ intelligence levels, and some relevant designs for human experiments. The main theme of this review is to show that by combining theory, agent-based modeling, and controlled human experiments, one can garner more reliable and credible results on account of a better verification of theory; accordingly, this way, a wider range of economic and financial problems and phenomena can be studied.

关键词： agent-based modeling controlled human experiment minority game econophysics chaos,leverage business cycle

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Reopen schools safely:simulating COVID-19 transmission on campus with a contact network agent-based model

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International Journal of Digital Earth 2022年第1期15卷 381-396页

作者： Chuyao Liao Xiang Chen Li Zhuo Yuan Liu Haiyan Tao Christopher G.Burton Guangdong Provincial Engineering Research Center for Public Security and Disaster School of Geography and PlanningSun Yat-sen UniversityGuangzhouPeople’s Republic of China Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation Sun Yat-sen UniversityGuangzhouPeople’s Republic of China Department of Geography University of ConnecticutStorrsCTUSA Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) ZhuhaiPeople’s Republic of China Key Laboratory of Tropical Disease Control (Sun Yat-sen University) Ministry of EducationGuangzhouPeople’s Republic of China

As the COVID-19 vaccination has been quickly rolling out around the globe,the evaluation of the effects of vaccinating populations for the safe reopening of schools has become a focal point for educators,decision-makers,and the general public.Within this context,we develop a contact network agent-based model(CN-ABM)to simulate on-campus disease transmission scenarios.The CN-ABM establishes contact networks for agents based on their daily activity patterns,evaluates the agents’health status change in different activity environments,and then simulates the epidemic curve.By applying the model to a real-world campus environment,we identify how different community risk levels,teaching modalities,and vaccination rates would shape the epidemic curve.The results show that without vaccination,retaining under 50%of on-campus students can largely flatten the curve,and having 25%on-campus students can achieve the best result(peak value<1%).With vaccination,having a maximum of 75%on-campus students and at least a 45%vaccination rate can suppress the curve,and a 65%vaccination rate can achieve the best result.The developed CN-ABM can be employed to assist local government and school officials with developing proactive intervention strategies to safely reopen schools.

关键词： COVID-19 contact network vaccination agent-based modeling school

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On Effective Campus Attack Response:Insights from agent-based Simulation for Improving Emergency Information Sharing System Design and Response Strategy

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International Journal of Disaster Risk Science 2022年第3期13卷 435-447页

作者： Steven Beattie Jing Yang Sunny Xi Wai Kin Victor Chan Tsinghua-Berkeley Shenzhen Institute Tsinghua UniversityShenzhen518055China

Information sharing systems are a critical component of emergency response—especially in campus attack situations that unfold very rapidly.The design of effective information sharing systems is often difficult,however,due to a lack of data on these assault events.This work takes an agent-based approach to simulate three campus emergency information sharing system design alternatives in the context of a college campus knife attack,and incorporates data from on-campus student surveys and parameter tuning experiments.Alternatives are evaluated according to:(1)improved student attack response outcomes;and(2)effective institutional response to the attack.The results confirm that increased awareness supports rapid emergency reporting,but an important gap exists between students'awareness and their ability to respond effectively,which depends on a number of campus-specific factors.A strong positive impact is seen from safe and efficient information sharing with authorities.This impact depends largely on reporting system implementation qualities,as opposed to campus-specific factors.On a campus in China,WeChat was used as a basis for messaging models.The simulation results show a 9%drop in casualties and a 22%faster police response time from a text-based reporting system using‘‘base''WeChat features instead of traditional phone reporting.Our results also project a 30%drop in casualties and 52%faster police response time using a system designed around a WeChat Mini Program or standalone campus emergency reporting app.These outcomes suggest a number of recommendations for improving outdated campus emergency information-sharing systems and response strategies.

关键词： agent-based impact analysis agent-based modeling Campus security Emergency response Information sharing

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modeling the impact of changing sexual behaviors with opposite-sex partners and STI testing among women and men ages 15-44 on STI diagnosis rates in the United States 2012-2019

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Infectious Disease Modelling 2023年第4期8卷 1169-1176页

作者： Deven T.Hamilton David A.Katz Laura T.Haderxhanaj Casey E.Copen Ian H.Spicknall Matthew Hogben Center for Studies in Demography and Ecology University of WashingtonSeattleWAUSA Department of Global Health University of WashingtonSeattleWAUSA Division of STD Prevention National Center for HIV/AIDSHepatitisSexually Transmitted DiseaseTuberculosis PreventionCenters for Disease Control and PreventionAtlantaGAUSA

Objective:To estimate the potential contributions of reported changes in frequency of penile-vaginal sex(PVS),condom use and STI screening to changes in gonorrhea and chlamydial diagnoses from 2012 to 2019.Methods:An agent-based model of the heterosexual population in the U.S.simulated the STI epidemics.Baseline was calibrated to 2012 diagnosis rates,testing,condom use,and frequency of PVS.Counterfactuals used behaviors from the 2017-2019 NSFG,and we evaluated changes in diagnosis and incidence rates in 2019.Results:Higher testing rates increased gonorrhea and chlamydia diagnosis by 14%and 13%,respectively,but did not reduce incidence.Declining frequency of PVS reduced the diagnosis rate for gonorrhea and chlamydia 6%and 3%respectively while reducing incidence by 10%and 9%respectively.Declining condom use had negligible impact on diagnosis and incidence.Conclusion:Understanding how changing behavior drives STI incidence is essential to addressing the growing epidemics.Changes in testing and frequency of PVS likely contributed to some,but not all,of the changes in diagnoses.More research is needed to understand the context within which changing sexual behavior and testing are occurring.

关键词： Gonorrhea Chlamydia agent-based modeling Simulation

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On the applicability of various levels of detail for occupant behavior representation and modeling in building performance simulation

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建筑模拟(英文) 2023年第8期16卷 1481-1498页

作者： Jeetika Malik Handi Chandra Putra Kaiyu Sun Tianzhen Hong Building Technology and Urban System Division Lawrence Berkeley National LaboratoryBerkeleyCA 94720USA

Occupant behavior(OB)is one of the significant sources of uncertainty in building performance simulation.While OB modeling has received increased attention in the past decade,research on the degree of granularity or level of detail(LoD)required for representing occupants is still in the nascent stages.This paper analyzes the modeling and applicability of three LoDs to represent occupants in building performance assessment.A medium-sized prototype office building located in Chicago,Illinois is used as the simulation case study.Ten occupant-centric attributes are adopted to develop the LoDs for OB representation.We first demonstrate the different modeling approaches required for simulating the three fidelity levels.Later,we illustrate the suitability of the developed LoDs in supporting six building performance use cases across different lifecycle stages.This study intends to provide guidance for the building simulation community on appropriate OB representation to support various use cases.

关键词： occupant behavior agent-based modeling building performance simulation level of detail fit-for-purpose office buildings

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