Bhakti S. S. Onggo

Towards a unified conceptual model representation: a case study in healthcare

One of the critical success factors in a simulation project is good communication between different stakeholders in the project, especially in the early stages. Good documentation or representation is essential for communicating conceptual models between stakeholders effectively. Despite the lack of a single accepted definition for a conceptual model, most definitions agree that a conceptual model contains a set of components, each of which specifies different aspects of a conceptual model. This paper advocates the use of a standard multi-faceted representation of conceptual models. A number of diagrams are proposed to represent each of the conceptual model components. Our intention is to initiate discussion and the development of a standard multi-faceted conceptual model representation that will benefit stakeholders involved in a simulation project. A case study in healthcare is used to show how the proposed unified conceptual modelling representation can be applied in practice.

Agent-based conceptual model representation using BPMN

In a simulation project, a good conceptual model representation is critical for communicating conceptual models between stakeholders. A conceptual model describes the problem domain and model specifications. The description of the problem domain includes the objectives, inputs, outputs, content, assumptions and simplifications made in the model. The model specifications are used to specify the models behavior. This article focuses on the representation of the model content (structure, boundary and level of detail) component of an agent-based simulation (ABS) model. For this, we propose the use of Business Process Model and Notation (BPMN) from the Object Management Group. A Web-based visual modeling tool has been developed using JavaScript to demonstrate how BPMN can be used to represent an ABS conceptual model and how the tool translates the conceptual model into code ready for execution using Repast HPC.

Conservative simulation using distributed-shared memory

This paper focuses on conservative simulation using distributed-shared memory for inter-processor communication. JavaSpaces, a special service of Java Jini, provides a shared persistent memory for simulation message communication among processors. Two benchmark programs written using our SPaDES/Java parallel simulation library are used. The first program is a linear pipeline system representing a loosely-coupled open system. The PHOLD program represents a strongly-connected closed system. Experiments are carried out using a cluster of Pentium II PCs. We used a combination of Wood Turner carrier null, flushing and demand-driven algorithms for null message synchronization. To optimize message communication, we replace SPaDES/Java inter-processor communication implemented using Javas Remote Method Invocation (RMI) with one JavaSpace. For PHOLD (16x16, 16) running on eight processors, this change reduces simulation runtime by more than half, null message overhead reduces by a further 15%, and event rate more than doubled. Based on our memory analysis methodology, the memory cost of null message synchronization for PHOLD is less than 9% of the total memory needed by the simulation.

BPMN pattern for agent-based simulation model representation

The explicit representation of a conceptual model allows it to be communicated and analyzed by the stakeholders in a simulation project. When communication involves different types of stakeholders, a good representation that can be understood by all stakeholders is essential. Many existing methods for the conceptual model representation of agent-based simulation models are less friendly to business users. This paper advocates use of the Business Process Model and Notation diagrams for agent-based simulation conceptual model representation in the context of business applications. This paper also proposes a BPMN pattern that provides visual representation of an agent and its behavior represented as a set of internal and external functions.

Agent-based computational modelling of social risk responses

A characteristic aspect of risks in a complex, modern society is the nature and degree of the public response – sometimes significantly at variance with objective assessments of risk. A large part of the risk management task involves anticipating, explaining and reacting to this response. One of the main approaches we have for analysing the emergent public response, the social amplification of risk framework, has been the subject of little modelling. The purpose of this paper is to explore how social risk amplification can be represented and simulated. The importance of heterogeneity among risk perceivers, and the role of their social networks in shaping risk perceptions, makes it natural to take an agent-based approach. We look in particular at how to model some central aspects of many risk events: the way actors come to observe other actors more than external events in forming their risk perceptions; the way in which behaviour both follows risk perception and shapes it; and the way risk communications are fashioned in the light of responses to previous communications. We show how such aspects can be represented by availability cascades, but also how this creates further problems of how to represent the contrasting effects of informational and reputational elements, and the differentiation of private and public risk beliefs. Simulation of the resulting model shows how certain qualitative aspects of risk response time series found empirically – such as endogenously-produced peaks in risk concern – can be explained by this model.

Data identification and data collection methods in simulation: a case study at ORH Ltd

There seems to be paucity in the research into the collection of data for use in simulation. This is rather unfortunate since data quality and availability are two of the most challenging issues in many simulation projects. This paper discusses how simulation practitioners identify and collect data for simulation projects. The data was collected from ORH Ltd, a management consultancy company using participant observations method and an experiment using a mock case scenario. From the observation, we produce a generic data identification and collection method. The method is evaluated using a real project conducted for a UK Ambulance Service. The experiment reveals variations in the data identification process that are influenced by the role and the level of experience of modellers.

Effect of event orderings on memory requirement in parallel simulation

A new formal approach based on partial order set (poset) theory is proposed to analyze the space requirement of discrete-event parallel simulation. We divide the memory required by a simulation problem into memory to model the states of the real-world system, memory to maintain a list of future event occurrences, and memory required to implement the event synchronization protocol. We establish the relationship between poset theory and event orderings in simulation. Based on our framework, we analyze the space requirement using an open and a closed system as examples. Our analysis shows that apart from problem size and traffic intensity that affects the memory requirement, event ordering is an important factor that can be analyzed before implementation. In an open system, a weaker event ordered simulation requires more memory than strong ordering. However, the memory requirement is constant and independent of event ordering in closed systems.

Using agent-based simulation to analyse the effect of broadcast and narrowcast on public perception: a case in social risk amplification

Individuals often use information from broadcast news (e.g. media) and narrowcast news (e.g. personal social network) to form their perception on a certain social issue. Using a case study in social risk amplification, this paper demonstrates that simulation modelling, specifically agent-based simulation, can be useful in analysing the effect of broadcast and narrowcast processes on the formation of public risk perception. The first part of this paper explains the structure of a model that allows easy configuration for testing various behaviours about which the empirical literature cannot make definitive predictions. The second part of this paper discusses the effect of personal social network and the role of media in the dynamics of public risk perception. The results show the undesirable effect of the extreme narrowcast process in society and a media that simply broadcasts the average public risk perception.

Elements of a hybrid simulation model: a case study of the blood supply chain in low- and middle-income countries

A hybrid simulation model is a simulation model that is formed from at least two different simulation modelling methods (e.g. discrete event, system dynamics, agent-based). The use of different simulation modelling methods in one model requires modellers to specify additional model elements. This paper discusses three elements, namely, the modules, module interfaces and updating rules. Each module may use a different simulation method. The interface between modules defines the information that will be passed between them (including aggregation and disaggregation). The updating rules define how the information sent by one module affects other modules. These three elements are explained using a case study of a blood supply chain simulation model for low- and middle-income countries (LMIC) which has different characteristics and challenges in comparison to the typical blood supply chain in high-income countries (HIC).

Towards fully-facilitated discrete event simulation modelling: Addressing the model coding stage

Abstract The literature suggests that increasing stakeholder engagement has a positive impact on projects using discrete-event simulation in healthcare. This suggests projects should strive to involve the stakeholders in as much of the project as possible, through facilitated workshops. A notable gap in stakeholder involvement is the model coding stage, in which a conceptual model is turned into a discrete-event simulation model running on a computer. This paper investigates how and under what circumstances model coding might also be conducted in facilitated workshops, in particular through the use of the Business Process Model and Notation (BPMN) modelling standard. This work arose from a series of modelling projects with two hospitals, one in Italy and the other in the UK. The paper describes how BPMN can contribute, with a case in which model coding was achieved in a facilitated workshop and a second in which it was not but which highlights further barriers to this in some contexts. These barriers arise from the detail necessary for requisite modelling regarding (i) the level of complexity of the model and (ii) challenges in data access and analysis to populate the model. The relationship between the technical capabilities of tools available and the impact of these barriers is also discussed. We believe this is the first time that discrete-event simulation model coding in a facilitated workshop in healthcare has been described, and we provide a clear view of the further barriers. To indicate when facilitated model coding is currently achievable, we suggest a contextual matrix.