Modelling has been used extensively by all national governments and the World Health Organisation in deciding on the best strategies to pursue in mitigating the effects of COVID-19. Principally these have been epidemiological models aimed at understanding the spread of the disease and the impacts of different interventions. But a global pandemic generates a large number of problems and questions, not just those related to disease transmission, and each requires a different model to find the best solution. In this article we identify challenges resulting from the COVID-19 pandemic and discuss how simulation modelling could help to support decision-makers in making the most informed decisions. Modellers should see the article as a call to arms and decision-makers as a guide to what support is available from the simulation community.
ARTICLE HISTORY
Citation: TAKO, A.A. and ROBINSON, S., 2012. The application of discrete event simulation and system dynamics in the logistics and supply chain context. Decision Support Systems, 52 (4), pp. 802 -815.Additional Information:• This article was published in the journal, Decision Support Sys-
AbstractDiscrete event simulation (DES) and system dynamics (SD) are two modelling approaches widely used as decision support tools in logistics and supply chain management (LSCM). A widely held belief exists that SD is mostly used to model problems at a strategic level, whereas DES is used at an operational/tactical level. This paper explores the application of DES and SD as decision support systems (DSS) for LSCM by looking at the nature and level of issues modelled. Peer reviewed journal papers that use these modelling approaches to study supply chains, published between 1996 and 2006 are reviewed. A total of 127 journal articles are analysed to identify the frequency with which the two simulation approaches are used as modelling tools for DSS in LSCM. Our findings suggest that DES has been used more frequently to model supply chains, with the exception of the bullwhip effect, which is mostly modelled using SD. Based on the most commonly used modelling approach, issues in LSCM are categorised into four groups: the DES domain, the SD domain, the common domain and the less common domain. The study furthermore suggests that in terms of the level of decision making involved, strategic or operational/tactical, there is no difference in the use of either DES or SD. The results of this study inform the existing literature about the use of DES and SD as DSS tools in LSCM.
a b s t r a c tDiscrete event simulation (DES) studies in healthcare are thought to benefit from stakeholder participation during the study lifecycle. This paper reports on a multi-methodology framework, called PartiSim that is intended to support participative simulation studies. PartiSim combines DES, a traditionally hard OR approach, with soft systems methodology (SSM) in order to incorporate stakeholder involvement in the study lifecycle. The framework consists of a number of prescribed activities and outputs as part of the stages involved in the simulation lifecycle, which include study initiation, finding out about the problem, defining a conceptual model, model coding, experimentation and implementation. In PartiSim four of these stages involve facilitated workshops with a group of stakeholders. We explain the organisation of workshops, the key roles assigned to analysts and stakeholders, and how facilitation is embedded in the framework. We discuss our experience of using the framework, provide guidance on when to use it and conclude with future research directions.
Citation: TAKO, A.A. and ROBINSON, S., 2010
AbstractAn empirical study comparing the model development process followed by experts in DiscreteEvent Simulation (DES) and System Dynamics (SD) modelling is undertaken. Verbal Protocol Analysis (VPA) is used to study the modelling process followed by ten expert modellers (5 SD and 5 DES). Participants are asked to build simulation models based on a case study and to think aloud while modelling. The generated verbal protocols are divided into 7 modelling topics:problem structuring, conceptual modelling, data inputs, model coding, validation & verification,results & experimentation and implementation and then analyzed. Our results suggest that all modellers switch between modelling topics, however DES modellers follow a more linear progression. DES modellers focus significantly more on model coding and verification & validation, whereas SD modellers on conceptual modelling. Observations are made revealing some interesting differences in the way the two groups of modellers tackle the case. This paper contributes towards the comparison of DES and SD.
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