| 期刊全称 | Agent-based Modeling and Simulation | | 影响因子2023 | Simon J. E. Taylor | | 视频video | http://file.papertrans.cn/152/151148/151148.mp4 | | 学科分类 | OR Essentials | | 图书封面 |  | | 影响因子 | Operational Research (OR) deals with the use of advanced analytical methods to support better decision-making. It is multidisciplinary with strong links to management science, decision science, computer science and many application areas such as engineering, manufacturing, commerce and healthcare. In the study of emergent behaviour in complex adaptive systems, Agent-based Modelling & Simulation (ABMS) is being used in many different domains such as healthcare, energy, evacuation, commerce, manufacturing and defense. This collection of articles presents a convenient introduction to ABMS with papers ranging from contemporary views to representative case studies. The OR Essentials series presents a unique cross-section of high quality research work fundamental to understanding contemporary issues and research across a range of Operational Research (OR) topics. It brings together some of the best research papers from the esteemed Operational Research Society and its associated journals, also published by Palgrave Macmillan. | | Pindex | Book 2014 |
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Front Matter |
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Abstract
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| 2 |
,Introducing agent-based modeling and simulation, |
Simon J. E. Taylor |
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Abstract
The manager of an Accident and Emergency(A&E) service(or Emergency Room) has a problem. The waiting room of her Unit is always full of patients waiting to see her clinical staff. Patients arrive, are checked in by a receptionist and then wait until they are seen by a nurse. If an arriving patient is in obvious distress then the patient is seen as soon as a nurse is available. The nurse records their medical details, discusses them with a doctor and then proceeds with a range of possible actions to treat the patient or to pass the patient on to another department. How can the manager understand how to reduce the number of patients waiting to see the nurse? Should she hire more nurses? Are doctors in short supply?Are nurses waiting for information from other departments? What about alternative arrival arrangements—should the reception team have clinical skills to make an earlier assessment of patients’ needs? Modeling & simulation (M&S) makes it possible for the A&E manager to create a verifiable and valid computer model of her system and to simulate it under different experimental conditions to understand what is causing the lengthy waiting times and the possible impact of different
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,Tutorial on agent-based modeling and simulation, |
C. M. Macal,M. J. North |
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Abstract
Agent-based modeling and simulation (ABMS) is a relatively new approach to modeling systems composed of autonomous, interacting agents. Agent-based modeling is a way to model the dynamics of complex systems and complex adaptive systems. Such systems often self-organize themselves and create emergent order. Agent-based models also include models of behaviour (human or otherwise) and are used to observe the collective effects of agent behaviours and interactions. The development of agent modeling tools, the availability of micro-data, and advances in computation have made possible a growing number of agent-based applications across a variety of domains and disciplines. This article provides a brief introduction to ABMS, illustrates the main concepts and foundations, discusses some recent applications across a variety of disciplines, and identifies methods and toolkits for developing agent models.
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,Some insights into the emergence of agent-based modeling, |
B. L. Heath,R. R. Hill |
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Abstract
Agent-based modeling (ABM) has become a popular simulation analysis tool and has been used to examine systems from myriad domains. This article re-examines some of the scientific developments in computers, complexity, and systems thinking that helped lead to the emergence of ABM by shedding new light onto some old theories and connecting them to several key ABM principles of today. As it is often the case, examining history can lead to insightful views about the past, present, and the future. Thus, themes from cellular automata and complexity, cybernetics and chaos, and complex adaptive systems are examined and placed in historical context to better establish the application, capabilities, understanding, and future of ABM.
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,An application of agent-based simulation to the management of hospital-acquired infection, |
Y. Meng,R. Davies,K. Hardy,P. Hawkey |
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Abstract
Hospital patients who are colonized with methicillin-resistant Staphylococcus aureus (MRSA), may transmit the bacteria to other patients. An agent-based simulation is designed to determine how the problem might be managed and the risk of transmission reduced. Most MRSA modeling studies have applied mathematical compartmental models or Monte Carlo simulations. In the agent-based model, each patient is identified on admission as being colonized or not, has a projected length of stay and may be more or less susceptible to colonization. Patient states represent colonization, detection, treatment, and location within the ward. MRSA transmission takes place between pairs of individuals in successive time slices. Various interventions designed to reduce MRSA transmission are embedded in the model including: admission and repeat screening tests, shorter test turnaround time, isolation, and decolonization treatment. These interventions can be systematically evaluated by model experimentation.
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,An agent-based simulation approach for the new product diffusion of a novel biomass fuel, |
M. Günther,C. Stummer,L. M. Wakolbinger,M. Wildpaner |
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Abstract
Marketing activities support the market introduction of innovative goods or services by furthering their diffusion and, thus, their success. However, such activities are rather expensive. Managers must therefore decide which specific marketing activities to apply to which extent and/or to which target group at which point in time. In this paper, we introduce an agent-based simulation approach that supports decision-makers in these concerns. The practical applicability of our tool is illustrated by means of a case study of a novel, biomass-based fuel that will likely be introduced on the Austrian market within the next 5 years.
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,Agent-based modeling and simulation of urban evacuation: relative effectiveness of simultaneous and |
X. Chen,F. B. Zhan |
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Abstract
This study investigates the effectiveness of simultaneous and staged evacuation strategies using agent-based simulation. In the simultaneous strategy, all residents are informed to evacuate simultaneously, whereas in the staged evacuation strategy, residents in different zones are organized to evacuate in an order based on different sequences of the zones within the affected area. This study uses an agent-based technique to model traffic flows at the level of individual vehicles and investigates the collective behaviours of evacuating vehicles. We conducted simulations using a microscopic simulation system called Paramics on three types of road network structures under different population densities. The three types of road network structures include a grid road structure, a ring road structure, and a real road structure from the City of San Marcos, Texas. Default rules in Paramics were used for trip generation, destination choice, and route choice. Simulation results indicate that (1) there is no evacuation strategy that can be considered as the best strategy across different road network structures, and the performance of the strategies depends on both road network structure and
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,Towards the development of a simulator for investigating the impact of people management practices |
P. O. Siebers,U. Aickelin,H. Celia,C. W. Clegg |
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Abstract
Models to understand the impact of management practices on retail performance are often simplistic and assume low levels of noise and linearity. Of course, in real life, retail operations are dynamic, nonlinear and complex. To overcome these limitations, we investigate discrete-event and agent-based modeling and simulation approaches. The joint application of both approaches allows us to develop simulation models that are heterogeneous and more life-like, though poses a new research question: When developing such simulation models one still has to abstract from the real world, however, ideally in such a way that the ‘essence’ of the system is still captured. The question is how much detail is needed to capture this essence, as simulation models can be developed at different levels of abstraction. In the literature the appropriate level of abstraction for a particular case study is often more of an art than a science. In this paper, we aim to study this question more systematically by using a retail branch simulation model to investigate which level of model accuracy obtains meaningful results for practitioners. Our results show the effects of adding different levels of detail and w
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,A multi-agent simulation of the pharmaceutical supply chain, |
G. Jetly,C. L. Rossetti,R. Handfield |
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Abstract
The pharmaceutical supply chain is composed of multiple firms interacting to produce and distribute drugs in an uncertain environment. In this work, we develop and validate a multi-agent simulation of the supply chains associated with the pharmaceutical industry. We demonstrate that the operating norms of a particular industry can be accurately represented to create an industry-specific model capable of tracing its evolution. Our model is initialized using 1982 financial data with 30 manufacturers, 60 suppliers, and 60 distributors. Three types of drugs, blockbusters, medium and small, with a 12-year lognormal product life cycle are released by manufacturers. Each quarter the distributors bid for future market share of the released products, and the suppliers bid for acceptable margins. Mergers and acquisitions, based on assets and expected profitability, are allowed at each level. One thousand replications, each lasting the equivalent of 39 years, are used to validate the model.
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,Workflow scheduling using multi-agent systems in a dynamically changing environment, |
M. Merdan,T. Moser,W. Sunindyo,S. Biffl,P. Vrba |
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Abstract
The application of intelligent agent technologies is considered a promising approach to improve system performance in complex and changeable environments. Especially, in the case of unforeseen events, for example, machine breakdowns that usually lead to a deviation from the initial production schedule, a multi-agent approach can be used to enhance system flexibility and robustness. In this paper we apply this approach to revise and re-optimize the dynamic system schedule in response to unexpected events. We employ Multi-Agent System simulation to optimize the total system output (eg, number of finished products) for recovery from machine and/or conveyor failure cases. Diverse types of failure classes (conveyor and machine failures), as well as duration of failures are used to test a range of dispatching rules in combination with the All Rerouting re-scheduling policy, which showed supreme performance in our previous studies. In this context, the Critical Ratio rule, which includes the transportation time into the calculation for the selection of the next job, outperformed all other dispatching rules. We also analyzed the impact of diverse simulation parameters (such as number of pa
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,Credit risk: an agent-based model of post-credit decision actions and credit losses in banks, |
S. Jonsson |
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Abstract
The credit crisis in 2007/2008 has increased the focus on bank credit risk. This paper uses an agent-based model (ABM) to investigate the impact of bankers’ post-credit decision actions on bank credit losses that are induced by lending to corporate clients. The banker agents are modeled according to results obtained from a survey that was distributed to bankers who are permitted to grant credit to firms. The results show that post-credit decision actions have substantial effects on bank credit losses, thus implying that regulators should consider organizational factors as a complement to bank assets when assigning capital requirements to banks. The study also aims to point to a new area of application of ABMs for both researchers and practitioners. Whereas previous research has used ABMs to simulate financial markets, this study suggests that financial organizations could be a vital area of application.
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,The development of new infantry tactics during the early eighteenth century: a computer simulation |
X. Rubio-Campillo,J. M. Cela,F. X. H. Cardona |
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Abstract
Computational models have been extensively used in military operations research, but they are rarely seen in military history studies. The introduction of this technique has potential benefits for the study of past conflicts. This paper presents an agent-based model (ABM) designed to help understand European military tactics during the eighteenth century, in particular during the War of the Spanish Succession. We use a computer simulation to evaluate the main variables that affect infantry performance in the battlefield, according to primary sources. The results show that the choice of a particular firing system was not as important as most historians state. In particular, it cannot be the only explanation for the superiority of Allied armies. The final discussion shows how ABM can be used to interpret historical data, and explores under which conditions the hypotheses generated from the study of primary accounts could be valid.
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,A generic testing framework for agent-based simulation models, |
Ö Gürcan,O. Dikenelli,C. Bernon |
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Abstract
Agent-based modeling and simulation (ABMS) had an increasing attention during the last decade. However, the weak validation and verification of agent-based simulation models makes ABMS hard to trust. There is no comprehensive tool set for verification and validation of agent-based simulation models, which demonstrates that inaccuracies exist and/or reveals the existing errors in the model. Moreover, on the practical side, many ABMS frameworks are in use. In this sense, we designed and developed a generic testing framework for agent-based simulation models to conduct validation and verification of models. This paper presents our testing framework in detail and demonstrates its effectiveness by showing its applicability on a realistic agent-based simulation case study.
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,Successful approaches for teaching agent-based simulation, |
C. M. Macal,M. J. North |
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Abstract
Agent-based simulation is a relatively new modeling technique that is being widely used by many disciplines to model complex adaptive systems. Few full-length courses exist on agent-based modeling, and a standard curriculum has not yet been established. But there is considerable demand to include agent-based modeling into simulation courses. Modelers often come to agent-based simulation (ABS) by way of self-study or attendance at tutorials and short courses. Although there is substantial overlap, there are many aspects of agent-based modeling that differ from discrete-event simulation and System Dynamics, including the applicable problem domains, the disciplines and backgrounds of students, and the underpinnings of its computational implementation. These factors make agent-based modeling difficult to include as an incremental add-on to existing simulation courses. This paper’s contribution is to report on some approaches to teaching ABS that the authors have successfully used in a range of classes and workshops.
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,Discrete-event simulation is alive and kicking!, |
S. Brailsford |
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Abstract
At the 2010 OR Society Simulation Workshop, there was a lively panel discussion entitled ‘Discrete-event simulation is dead, long live agent-based simulation!’, which was subsequently written up as a position paper for the Journal of Simulation (Siebers et al, 2010). This paper continues that discussion and, to quote Mark Twain, argues that rumours of the death of discrete-event simulation (DES) are greatly exaggerated. There has undoubtedly been a recent surge of interest within the mainstream OR community in the use of agent-based modeling, but this paper suggests that many of the cited benefits of agent-based simulation (ABS) can be achieved through the use of a traditional DES approach. These arguments are illustrated by several examples where DES has been used successfully to tackle ‘ABS-type’ problems.
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Back Matter |
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Abstract
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