Earthquake is a disastrous natural hazard that threatens numerous cities worldwide.The interval between the foreshock and the main event can sometimes last several minutes.Meanwhile,crowd emergency evacuation and find...Earthquake is a disastrous natural hazard that threatens numerous cities worldwide.The interval between the foreshock and the main event can sometimes last several minutes.Meanwhile,crowd emergency evacuation and finding shelter are vital for search and rescue managers.At the same time,many unpredicted challenges,such as the sudden increase in travel demand,shifts in public behavior,and the change in the regular transport supply,may arise due to evacuation conditions,which lead to different situations.This paper aims to introduce an approach for quick decision-making and timely evacuation response required by establishing a situation-aware system to minimize these risks and ensure the success of the evacuation plans,to support and predict current and future actions within the dynamic space of the crisis.The main contribution is innovating a Situation-Aware Emergency Evacuation(SAEE)model to enable crisis managers and evacuees to make the right decisions by providing timely and reliable information about the situation.This method is utilized in two situations:designing the emergency evacuation plan and finding the shortest/safest routes to reduce travel time for evacuees.Therefore,a hybrid approach is introduced,which involves a Fuzzy Inference System(FIS)and Deep Long Short-Term Memory(DLSTM)algorithm to identify,infer,and extract the existing situation at different levels(e.g.people,vehicles,and surroundings)after a foreshock using multi-agent-based simulation.The method proposed was simulated in the traffic network of District 6 of Tehran,the capital of Iran.The model results show that the evacuees'spatial knowledge and perception,as well as awareness of the situation of other agents and their surroundings,led to a significant(40%)reduction in the complete evacuation time.This time is considered the most pivotal factor in saving human lives and their arrival in safer areas.The role of situation awareness systems and increasing human cognition and perception can significantly help in this matter.展开更多
Emergencies, which are very difficult to be forecasted, would always bring about huge harm to people. Therefore, to find ways to reduce such devastating effects, researches on emergency management have turned to be pa...Emergencies, which are very difficult to be forecasted, would always bring about huge harm to people. Therefore, to find ways to reduce such devastating effects, researches on emergency management have turned to be paramount. Nowadays, the rapid development of computer technology has supplied a new and effective idea for the researches of emergency management, namely that the researches can be done in computers by performing simulation experiments according to the artificial societies, computational experiments, parallel execution （ACP） approach. Guided by this approach, this paper has proposed one agent-based prototype simulation system to research emergency management. Firstly, structure of the simulation system oriented to emergency management was analyzed and designed. Then a simulation system oriented to public health emergency management was constructed to study the transmission of infectious diseases. Finally, several experiments were carried out based on the system, with several significant conclusions having also been obtained.展开更多
With urban residents’increasing reliance on metro systems for commuting and other daily activities,extreme weather events such as heavy rainfall and flooding impacting the metro system services are becoming increasin...With urban residents’increasing reliance on metro systems for commuting and other daily activities,extreme weather events such as heavy rainfall and flooding impacting the metro system services are becoming increasingly of concern.Plans for such emergency interruptions require a thorough understanding of the potential outcomes on both the system and individual component scales.However,due to the complex dynamics,constraints,and interactions of the elements involved(e.g.,disaster,infrastructure,service operation,and travel behavior),there is still no framework that comprehensively evaluates the system performance across different spatiotemporal scales and is flexible enough to handle increasingly detailed travel behavior,transit service,and disaster information data.Built on an agent-based model(ABM)framework,this study adopts a data-driven ABM simulation approach informed by actual metro operation and travel demand data to investigate the impact of flood-induced station closures on travelers as well as the overall system response.A before-after comparison is conducted where the traveler behaviors in disaster scenarios are obtained from a discrete choice model of alternative stations and routes.A case study of the Shanghai Metro is used to demonstrate the ability of the proposed approach in evaluating the impacts of flood-induced station closures on individual traveler behavior under normal operation and a series of water level rise scenarios of up to 5m.It was found that,when the flood-induced station closures only affect a few river-side stations in the city center,the travelers experience only minor disruptions to their trips due to the availability of unaffected stations nearby as a backup.However,as the water level increases and more stations(mainly in the suburban area)are affected,up to 25%of trips are no longer being fulfilled due to the loss of entrances,exits,or transfer links.The system experiences overall less crowdedness in terms of passenger volume and platform waiting time with a few exceptions of increased passenger load due to concentrations of passenger flows to alternative stations under flooding-induced station closures.The proposed approach can be adapted to other disaster scenarios to reveal the disaster impacts on both aggregated and disaggregated levels and guide the design of more spatio-and temporally-targeted emergency plans for metro systems.展开更多
This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integrati...This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council(WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methods presented.展开更多
In game theoretic context, it is assumed that the decision maker has the extraordinary skills of reasoning and calculation. This assumption is called ＂perfect rationality＂. A player with perfect rationality can solv...In game theoretic context, it is assumed that the decision maker has the extraordinary skills of reasoning and calculation. This assumption is called ＂perfect rationality＂. A player with perfect rationality can solve complex problems without making mistakes. However, recently, many studies have restricted this rationality or the structure of game. These restrictions are called ＂bounded rationality.＂ The authors also focus on bounded rationality, but with learning dynamics and complex networks. A complex network covers a wide area. Currently, a wide range of studies have not only investigated network formation and the characteristics of a formed network, but also analyzed situations where a network is already provided. In addition, in an analysis using game theory, a prisoners＇ dilemma type game was used to investigate how a change in the network structure would affect the players＇ relationships Therefore, our model employs decision makers with learning dynamics and describes the interaction of decision makers as a network. The purpose of this study is to examine the behavior of the decision maker with learning dynamics and the formation of networks by the interaction of decision makers through an agent-based simulation.展开更多
Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(...Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(flexible,comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis(PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature,cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution(DS) and feed solution(FS)(known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process(PRO mode) can be efficiently evaluated using the NetL ogo platform.展开更多
Despite the growing interest in macroscopic epidemiological models to deal with threats posed by pandemics such as COVID-19,little has been done regarding the assessment of disease spread in day-to-day life,especially...Despite the growing interest in macroscopic epidemiological models to deal with threats posed by pandemics such as COVID-19,little has been done regarding the assessment of disease spread in day-to-day life,especially within buildings such as supermarkets where people must obtain necessities at the risk of exposure to disease.Here,we propose an integrated customer shopping simulator including both shopper movement and choice behavior,using a force-based and discrete choice model,respectively.By a simple extension to the force-based model,we implement the following preventive measures currently taken by supermarkets;social distancing and one-way systems,and different customer habits,assessing them based on the average individual disease exposure and the time taken to complete shopping(shopping efficiency).Results show that maintaining social distance is an effective way to reduce exposure,but at the cost of shopping efficiency.We find that the one-way system is the optimal strategy for reducing exposure while minimizing the impact on shopping efficiency.Customers should also visit supermarkets less frequently,but buy more when they do,if they wish to minimize their exposure.We hope that this work demonstrates the potential of pedestrian dynamics simulations in assessing preventative measures during pandemics,particularly if it is validated using empirical data.展开更多
The mission reliability assessment plays a great role in logistics planning and supporting resource optimization of complex system.But the current problem,which is difficult to solve,is how to model and analyze the ch...The mission reliability assessment plays a great role in logistics planning and supporting resource optimization of complex system.But the current problem,which is difficult to solve,is how to model and analyze the characters of system reliability under the complex mission profile.In order to solve the problem,an agentbased simulation method was used to assess reliability for complex systems with various random working conditions.A multi-working condition simulation agent(MA)was designed and used to simulate the random transferring process of working conditions of system,and it cooperated with system simulation agents(SAs)and unit simulation agents(UAs)to realize system mission reliability(MR)simulation.Through simulation experiments,effect of multiple working conditions mission on the reliability of system was analyzed by comparing with the basic reliability condition.Feasibility and efficiency of the method were proved through simulation experiments of the case system.The research result provides a viable and useful method and a solution for MR analysis and assessment of complex systems in multi-working conditions,which can help to evaluate the reliability of operating system orienting to the practical mission and environment,and it is meaningful for the reliability analysis and the design of complex systems.展开更多
Healthcare collaboration is crucial for reducing medical errors and ensuring patient safety,and effective collaboration is closely linked to visibility.However,research on how floor plans affect visibility among healt...Healthcare collaboration is crucial for reducing medical errors and ensuring patient safety,and effective collaboration is closely linked to visibility.However,research on how floor plans affect visibility among healthcare members(VHM)in inpatient care units is still insufficient,complicating architectural design decisions.This stems from the lack of methods to assess VHM in inpatient care units,where healthcare members'movements continuously alter their relative positions and visual relationships.This study proposes a novel method integrating agent-based simulation and social network analysis to assess VHM.The method first collects behavioral data from healthcare members to execute agent-based simulation.Subsequently,the simulated positions of healthcare members are used to construct visibility networks.Finally,social network analysis is applied to evaluate the VHM.The findings indicate:(1)the“multi-ring+branching”corridor shape exhibits the highest visibility;(2)shared staff stations improve visibility across different healthcare professionals;(3)spatial relationships between nurse stations and assigned patient rooms affect visibility disparities;(4)mobile nursing stations and interconnected support areas enhance visual communication across disparate zones.This research provides the first quantitative analysis of floor plan effects on VHM.The proposed method offers broad applicability for enhancing visibility assessment,improving healthcare collaboration and reducing medical errors.展开更多
The reduction of speed limits in urban roads through traffic calming schemes intends to ensure safer traffic conditions among road users by reducing the probability related to the occurrence of severe accident.Looking...The reduction of speed limits in urban roads through traffic calming schemes intends to ensure safer traffic conditions among road users by reducing the probability related to the occurrence of severe accident.Looking it from a different perspective,traffic calming measures can potentially resolve congestion problems at the same time by lowering the overall accessibility and attractiveness of private cars in urban areas.This study proposes a new methodological approach to explore and assess the direct impacts of traffic calming in the transport system efficiency of a metropolitan area.The multi-agent transport simulation(MATSim)and Open-Berlin scenario are utilized to perform this simulation experiment.By developing a new external tool,the free flow speed and road capacity of each network link is updated based on new speed limits and different compliance rates,which are defined per road hierarchy level.The test scenarios that are formulated present radical conditions,where the speed limit in most urban roads of Berlin drops to 30 km/h or even 15 km/h.The findings of this study show a considerably high increase in trips,passenger hours,and passenger kilometers using public transport modes,when traffic calming links are introduced,the reserve change is observed in private cars trips.Although the speed limits are decreased in inner urban roads in most of the scenarios,the decrease of average travel speed of private cars is not so high as it was expected.Surprisingly,private cars are used for longer distances in all test scenarios.Car drivers seem to use already existed motorways and private road to commute.In simulations,driver compliance to the new speed limits seems to be a determinant factor that is strongly influenced by the design interventions applied in a traffic calming area.展开更多
Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to i...Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.展开更多
With the development of electricity market mechanism and advanced metering infrastructure(AMI),demand response has become an important alternative solution to improving power system reliability and effi-ciency. In thi...With the development of electricity market mechanism and advanced metering infrastructure(AMI),demand response has become an important alternative solution to improving power system reliability and effi-ciency. In this paper, the agent-based modelling and simulation method is applied to explore the impact of symmetric market mechanism and demand response on electricity market. The models of market participants are established according to their behaviors. Consumers’ response characteristics under time-of-use(TOU) mechanism are also taken into account. The level of clearing price and market power are analyzed and compared under symmetric and asymmetric market mechanisms. The results indicate that the symmetric mechanism could effectively lower market prices and avoid monopoly.Besides, TOU could apparently flatten the overall demand curve by enabling customers to adjust their load profiles,which also helps to reduce the price.展开更多
This paper adopts agent-based simulation to study the horizontal competition among homogenous price-setting retailers in a one-to-many supply chain (a supply chain consists of one supplier and multiple retailers). W...This paper adopts agent-based simulation to study the horizontal competition among homogenous price-setting retailers in a one-to-many supply chain (a supply chain consists of one supplier and multiple retailers). We model the supplier and retailers as agents, and design their behavioral rules respectively. The results show that although the agents learn individually based on their own experiences, the system converges asymptotically to near Nash equilibrium steady states. When analyzing the results, we first discuss the properties of these steady states. Then based on these properties, we analyze the effects of the retailers’ horizontal competition on the retail prices, retailers’ profits and supplier’s revenue.展开更多
To simulate the rumor propagation process on online social network during emergency, a new rumor propagation model was built based on active immune mechanism. The rumor propagation mechanisms were analyzed and corresp...To simulate the rumor propagation process on online social network during emergency, a new rumor propagation model was built based on active immune mechanism. The rumor propagation mechanisms were analyzed and corresponding parameters were defined. BA scale free network and NW small world network that can be used for representing the online social network structure were constructed and their characteristics were compared. Agent-based simulations were conducted on both networks and results show that BA scale free network is more conductive to spreading rumors and it can facilitate the rumor refutation process at the same time. Rumors paid attention to by more people is likely to spread quicker and broader but for which the rumor refutation process will be more effective. The model provides a useful tool for understanding and predicting the rumor propagation process on online social network during emergency, providing useful instructions for rumor propagation intervention.展开更多
The transit bus environment is considered one of the primary sources of transmission of the COVID-19(SARSCoV-2)virus.Modeling disease transmission in public buses remains a challenge,especially with uncertainties in p...The transit bus environment is considered one of the primary sources of transmission of the COVID-19(SARSCoV-2)virus.Modeling disease transmission in public buses remains a challenge,especially with uncertainties in passenger boarding,alighting,and onboard movements.Although there are initial findings on the effectiveness of some of the mitigation policies(such as face-covering and ventilation),evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways,boarding and alighting patterns,and seating capacity control.This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic in USA,in which it brings crucial insights on combating current and future epidemics.We use an agent-based simulation model(ABSM)based on standard design characteristics for urban buses in USA and two different service frequency settings(10-min and 20-min headways).We find that wearing face-coverings(surgical masks)significantly reduces onboard transmission rates,from no mitigation rates of 85%in higher-frequency buses and 75%in lower-frequency buses to 12.5%.The most effective prevention outcome is the combination of KN-95 masks,open window policies,and half-capacity seating control during higher-frequency bus services,with an outcome of nearly 0%onboard infection rate.Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design,which is crucial to ensuring passenger safety.The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies.展开更多
文摘Earthquake is a disastrous natural hazard that threatens numerous cities worldwide.The interval between the foreshock and the main event can sometimes last several minutes.Meanwhile,crowd emergency evacuation and finding shelter are vital for search and rescue managers.At the same time,many unpredicted challenges,such as the sudden increase in travel demand,shifts in public behavior,and the change in the regular transport supply,may arise due to evacuation conditions,which lead to different situations.This paper aims to introduce an approach for quick decision-making and timely evacuation response required by establishing a situation-aware system to minimize these risks and ensure the success of the evacuation plans,to support and predict current and future actions within the dynamic space of the crisis.The main contribution is innovating a Situation-Aware Emergency Evacuation(SAEE)model to enable crisis managers and evacuees to make the right decisions by providing timely and reliable information about the situation.This method is utilized in two situations:designing the emergency evacuation plan and finding the shortest/safest routes to reduce travel time for evacuees.Therefore,a hybrid approach is introduced,which involves a Fuzzy Inference System(FIS)and Deep Long Short-Term Memory(DLSTM)algorithm to identify,infer,and extract the existing situation at different levels(e.g.people,vehicles,and surroundings)after a foreshock using multi-agent-based simulation.The method proposed was simulated in the traffic network of District 6 of Tehran,the capital of Iran.The model results show that the evacuees'spatial knowledge and perception,as well as awareness of the situation of other agents and their surroundings,led to a significant(40%)reduction in the complete evacuation time.This time is considered the most pivotal factor in saving human lives and their arrival in safer areas.The role of situation awareness systems and increasing human cognition and perception can significantly help in this matter.
基金supported by National Natural Science Foundation of China(Nos.91024030 and 91224008)
文摘Emergencies, which are very difficult to be forecasted, would always bring about huge harm to people. Therefore, to find ways to reduce such devastating effects, researches on emergency management have turned to be paramount. Nowadays, the rapid development of computer technology has supplied a new and effective idea for the researches of emergency management, namely that the researches can be done in computers by performing simulation experiments according to the artificial societies, computational experiments, parallel execution （ACP） approach. Guided by this approach, this paper has proposed one agent-based prototype simulation system to research emergency management. Firstly, structure of the simulation system oriented to emergency management was analyzed and designed. Then a simulation system oriented to public health emergency management was constructed to study the transmission of infectious diseases. Finally, several experiments were carried out based on the system, with several significant conclusions having also been obtained.
基金supported by the Natural Sciences and Engineering Research Council of Canada Discovery Grant(NSERC RGPIN-2022-05028 and DGECR-2022-00522)supported by the“National Natural Science Foundation of China(No.72001162)”。
文摘With urban residents’increasing reliance on metro systems for commuting and other daily activities,extreme weather events such as heavy rainfall and flooding impacting the metro system services are becoming increasingly of concern.Plans for such emergency interruptions require a thorough understanding of the potential outcomes on both the system and individual component scales.However,due to the complex dynamics,constraints,and interactions of the elements involved(e.g.,disaster,infrastructure,service operation,and travel behavior),there is still no framework that comprehensively evaluates the system performance across different spatiotemporal scales and is flexible enough to handle increasingly detailed travel behavior,transit service,and disaster information data.Built on an agent-based model(ABM)framework,this study adopts a data-driven ABM simulation approach informed by actual metro operation and travel demand data to investigate the impact of flood-induced station closures on travelers as well as the overall system response.A before-after comparison is conducted where the traveler behaviors in disaster scenarios are obtained from a discrete choice model of alternative stations and routes.A case study of the Shanghai Metro is used to demonstrate the ability of the proposed approach in evaluating the impacts of flood-induced station closures on individual traveler behavior under normal operation and a series of water level rise scenarios of up to 5m.It was found that,when the flood-induced station closures only affect a few river-side stations in the city center,the travelers experience only minor disruptions to their trips due to the availability of unaffected stations nearby as a backup.However,as the water level increases and more stations(mainly in the suburban area)are affected,up to 25%of trips are no longer being fulfilled due to the loss of entrances,exits,or transfer links.The system experiences overall less crowdedness in terms of passenger volume and platform waiting time with a few exceptions of increased passenger load due to concentrations of passenger flows to alternative stations under flooding-induced station closures.The proposed approach can be adapted to other disaster scenarios to reveal the disaster impacts on both aggregated and disaggregated levels and guide the design of more spatio-and temporally-targeted emergency plans for metro systems.
文摘This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council(WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methods presented.
文摘In game theoretic context, it is assumed that the decision maker has the extraordinary skills of reasoning and calculation. This assumption is called ＂perfect rationality＂. A player with perfect rationality can solve complex problems without making mistakes. However, recently, many studies have restricted this rationality or the structure of game. These restrictions are called ＂bounded rationality.＂ The authors also focus on bounded rationality, but with learning dynamics and complex networks. A complex network covers a wide area. Currently, a wide range of studies have not only investigated network formation and the characteristics of a formed network, but also analyzed situations where a network is already provided. In addition, in an analysis using game theory, a prisoners＇ dilemma type game was used to investigate how a change in the network structure would affect the players＇ relationships Therefore, our model employs decision makers with learning dynamics and describes the interaction of decision makers as a network. The purpose of this study is to examine the behavior of the decision maker with learning dynamics and the formation of networks by the interaction of decision makers through an agent-based simulation.
文摘Forward osmosis(FO), as an emerging technology, is influenced by different factors such as operating conditions,module characteristics, and membrane properties. The general aim of this study was to develop a suitable(flexible,comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis(PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature,cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution(DS) and feed solution(FS)(known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process(PRO mode) can be efficiently evaluated using the NetL ogo platform.
基金Project supported by the China Scholarship Council(Grant No.201906370050).
文摘Despite the growing interest in macroscopic epidemiological models to deal with threats posed by pandemics such as COVID-19,little has been done regarding the assessment of disease spread in day-to-day life,especially within buildings such as supermarkets where people must obtain necessities at the risk of exposure to disease.Here,we propose an integrated customer shopping simulator including both shopper movement and choice behavior,using a force-based and discrete choice model,respectively.By a simple extension to the force-based model,we implement the following preventive measures currently taken by supermarkets;social distancing and one-way systems,and different customer habits,assessing them based on the average individual disease exposure and the time taken to complete shopping(shopping efficiency).Results show that maintaining social distance is an effective way to reduce exposure,but at the cost of shopping efficiency.We find that the one-way system is the optimal strategy for reducing exposure while minimizing the impact on shopping efficiency.Customers should also visit supermarkets less frequently,but buy more when they do,if they wish to minimize their exposure.We hope that this work demonstrates the potential of pedestrian dynamics simulations in assessing preventative measures during pandemics,particularly if it is validated using empirical data.
文摘The mission reliability assessment plays a great role in logistics planning and supporting resource optimization of complex system.But the current problem,which is difficult to solve,is how to model and analyze the characters of system reliability under the complex mission profile.In order to solve the problem,an agentbased simulation method was used to assess reliability for complex systems with various random working conditions.A multi-working condition simulation agent(MA)was designed and used to simulate the random transferring process of working conditions of system,and it cooperated with system simulation agents(SAs)and unit simulation agents(UAs)to realize system mission reliability(MR)simulation.Through simulation experiments,effect of multiple working conditions mission on the reliability of system was analyzed by comparing with the basic reliability condition.Feasibility and efficiency of the method were proved through simulation experiments of the case system.The research result provides a viable and useful method and a solution for MR analysis and assessment of complex systems in multi-working conditions,which can help to evaluate the reliability of operating system orienting to the practical mission and environment,and it is meaningful for the reliability analysis and the design of complex systems.
基金funded by the National Natural Science Foundation of China(Grant No.51978143)。
文摘Healthcare collaboration is crucial for reducing medical errors and ensuring patient safety,and effective collaboration is closely linked to visibility.However,research on how floor plans affect visibility among healthcare members(VHM)in inpatient care units is still insufficient,complicating architectural design decisions.This stems from the lack of methods to assess VHM in inpatient care units,where healthcare members'movements continuously alter their relative positions and visual relationships.This study proposes a novel method integrating agent-based simulation and social network analysis to assess VHM.The method first collects behavioral data from healthcare members to execute agent-based simulation.Subsequently,the simulated positions of healthcare members are used to construct visibility networks.Finally,social network analysis is applied to evaluate the VHM.The findings indicate:(1)the“multi-ring+branching”corridor shape exhibits the highest visibility;(2)shared staff stations improve visibility across different healthcare professionals;(3)spatial relationships between nurse stations and assigned patient rooms affect visibility disparities;(4)mobile nursing stations and interconnected support areas enhance visual communication across disparate zones.This research provides the first quantitative analysis of floor plan effects on VHM.The proposed method offers broad applicability for enhancing visibility assessment,improving healthcare collaboration and reducing medical errors.
文摘The reduction of speed limits in urban roads through traffic calming schemes intends to ensure safer traffic conditions among road users by reducing the probability related to the occurrence of severe accident.Looking it from a different perspective,traffic calming measures can potentially resolve congestion problems at the same time by lowering the overall accessibility and attractiveness of private cars in urban areas.This study proposes a new methodological approach to explore and assess the direct impacts of traffic calming in the transport system efficiency of a metropolitan area.The multi-agent transport simulation(MATSim)and Open-Berlin scenario are utilized to perform this simulation experiment.By developing a new external tool,the free flow speed and road capacity of each network link is updated based on new speed limits and different compliance rates,which are defined per road hierarchy level.The test scenarios that are formulated present radical conditions,where the speed limit in most urban roads of Berlin drops to 30 km/h or even 15 km/h.The findings of this study show a considerably high increase in trips,passenger hours,and passenger kilometers using public transport modes,when traffic calming links are introduced,the reserve change is observed in private cars trips.Although the speed limits are decreased in inner urban roads in most of the scenarios,the decrease of average travel speed of private cars is not so high as it was expected.Surprisingly,private cars are used for longer distances in all test scenarios.Car drivers seem to use already existed motorways and private road to commute.In simulations,driver compliance to the new speed limits seems to be a determinant factor that is strongly influenced by the design interventions applied in a traffic calming area.
基金supported by the Shanghai Philosophy and Social Science Foundation(2022ECK004)Shanghai Soft Science Research Project(23692123400)。
文摘Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.
基金supported by National Natural Science Foundation of China(No.51577115)the Ministry of Industry and Information Technology of the People’s Republic of China(No.2016YFB0901302)
文摘With the development of electricity market mechanism and advanced metering infrastructure(AMI),demand response has become an important alternative solution to improving power system reliability and effi-ciency. In this paper, the agent-based modelling and simulation method is applied to explore the impact of symmetric market mechanism and demand response on electricity market. The models of market participants are established according to their behaviors. Consumers’ response characteristics under time-of-use(TOU) mechanism are also taken into account. The level of clearing price and market power are analyzed and compared under symmetric and asymmetric market mechanisms. The results indicate that the symmetric mechanism could effectively lower market prices and avoid monopoly.Besides, TOU could apparently flatten the overall demand curve by enabling customers to adjust their load profiles,which also helps to reduce the price.
基金This work was supported partly by the National Science Foundation of China (NSFC) under Grant No.70231010 and 70321001.
文摘This paper adopts agent-based simulation to study the horizontal competition among homogenous price-setting retailers in a one-to-many supply chain (a supply chain consists of one supplier and multiple retailers). We model the supplier and retailers as agents, and design their behavioral rules respectively. The results show that although the agents learn individually based on their own experiences, the system converges asymptotically to near Nash equilibrium steady states. When analyzing the results, we first discuss the properties of these steady states. Then based on these properties, we analyze the effects of the retailers’ horizontal competition on the retail prices, retailers’ profits and supplier’s revenue.
基金Supported by the National Natural Science Foundation of China(51374242,51504286)China Postdoctoral Science Foundation(2015M572270)the Fundamental Research Funds for the Central Universities of Central South University(2015zzts079)
文摘To simulate the rumor propagation process on online social network during emergency, a new rumor propagation model was built based on active immune mechanism. The rumor propagation mechanisms were analyzed and corresponding parameters were defined. BA scale free network and NW small world network that can be used for representing the online social network structure were constructed and their characteristics were compared. Agent-based simulations were conducted on both networks and results show that BA scale free network is more conductive to spreading rumors and it can facilitate the rumor refutation process at the same time. Rumors paid attention to by more people is likely to spread quicker and broader but for which the rumor refutation process will be more effective. The model provides a useful tool for understanding and predicting the rumor propagation process on online social network during emergency, providing useful instructions for rumor propagation intervention.
文摘The transit bus environment is considered one of the primary sources of transmission of the COVID-19(SARSCoV-2)virus.Modeling disease transmission in public buses remains a challenge,especially with uncertainties in passenger boarding,alighting,and onboard movements.Although there are initial findings on the effectiveness of some of the mitigation policies(such as face-covering and ventilation),evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways,boarding and alighting patterns,and seating capacity control.This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic in USA,in which it brings crucial insights on combating current and future epidemics.We use an agent-based simulation model(ABSM)based on standard design characteristics for urban buses in USA and two different service frequency settings(10-min and 20-min headways).We find that wearing face-coverings(surgical masks)significantly reduces onboard transmission rates,from no mitigation rates of 85%in higher-frequency buses and 75%in lower-frequency buses to 12.5%.The most effective prevention outcome is the combination of KN-95 masks,open window policies,and half-capacity seating control during higher-frequency bus services,with an outcome of nearly 0%onboard infection rate.Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design,which is crucial to ensuring passenger safety.The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies.
