A history of simulation development in the United Kingdom

Hollocks, Brian

doi:10.1109/wsc.2017.8247321

Cited by 4 publications

(4 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Indeed, our own field of operations research/management science owes much of its existence to the rapid increase in computer power over recent decades, enabling algorithms and simulations to be implemented on a scale that would previously have been impossible using only the capacity of humans. Histories of simulation modelling demonstrate the close correspondence of developments in modelling with improvements in computing (Robinson, 2005;Pidd and Carvalho, 2006;Hollocks, 2008Hollocks, , 2017Nance and Overstreet, 2017).…”

Section: Robinsonmentioning

confidence: 99%

Historical and Philosophical Perspectives on the Activity of Modelling

Robinson¹

2023

Proceedings of SW21 the OR Society Simulation Workshop

View full text Add to dashboard Cite

The activity of modelling entails the conception, representation and execution of a model. In this paper we explore this activity from a historical perspective, by positioning it within the philosophy of science, and by taking a practice-based perspective. We draw a clear distinction between the internal and implicit conceptual model that exists within the mind of the modeller, and its external and explicit representational and executable forms. As a field we have focused much of our efforts on model representation and execution, while largely skirting around the processes that lie behind how models are conceived. Ultimately, better understanding these processes is important for improving the practice of modelling.

show abstract

Section: Robinsonmentioning

confidence: 99%

Historical and Philosophical Perspectives on the Activity of Modelling

Robinson¹

2023

Proceedings of SW21 the OR Society Simulation Workshop

View full text Add to dashboard Cite

show abstract

“…Indeed, our own field of operations research/management science owes much of its existence to the rapid increase in computer power over recent decades, enabling algorithms and simulations to be implemented on a scale that would previously have been impossible using only the capacity of humans. Histories of simulation modelling demonstrate the close correspondence of developments in modelling with improvements in computing Pidd and Carvalho, 2006;Hollocks, 2008Hollocks, , 2017Nance and Overstreet, 2017).…”

Section: Robinsonmentioning

confidence: 99%

Proceedings of SW21 The OR Society Simulation Workshop

2023

View full text Add to dashboard Cite

Simulation, and now digital twins, excel in estimating parameters associated with complex and timedependent stochastic processes, e.g., large airport, highway, and warehouse operations. Within such contexts, we consider statistical inference, whereby one seeks to quantify the error in the obtained simulation estimate. Historically, statistical inference in simulation has been considered challenging because parameters needing estimation are often complicated, and simulation output often autocorrelated and non-normal. However, we argue that the remarkably simple idea of batching can be used as an "omnibus" inference device in simulation settings. Batching for inference works in three simple steps: (i) divide simulation output data into overlapping batches; (ii) construct parameter estimates from each batch; and (iii) use the batch estimates, after accounting for dependence, to perform statistical inference. As we describe in this paper, the resulting procedures are usually trivial to implement in software, and are provably correct and efficient. Batching ideas originated in the 1950s, and have enjoyed steady development in the simulation community since the 1970s mostly within the problem of variance estimation. Our thesis is that batching ideas have much wider utility, and that batching should be considered alongside other resampling ideas such as the bootstrap or the jackknife in modern statistics.

show abstract

“…12 The concepts of DES emerged in the late 1950s. 13 Conway et al 14 used M&S for queueing networks that represented manufacturing systems such as job shops, still one of the significant applications of DES. Conway et al 15 also began the academic discussion on DES, including discussions of the main characteristics of common DES models, the problems in constructing DES models with digital computers, and the issues of using DES models.…”

Section: Pre-1960smentioning

confidence: 99%

Past challenges and the future of discrete event simulation

Collins

Pour

Jordan

2021

Journal of Defense Modeling & Simulation

View full text Add to dashboard Cite

The American scientist Carl Sagan once said: “You have to know the past to understand the present.” We argue that having a meaningful dialogue on the future of simulation requires a baseline understanding of previous discussions on its future. For this paper, we conduct a review of the discrete event simulation (DES) literature that focuses on its future to understand better the path that DES has been following, both in terms of who is using simulation and what directions they think DES should take. Our review involves a qualitative literature review of DES and a quantitative bibliometric analysis of the Modeling and Simulation (M&S) literature. The results from the bibliometric study imply that demographics of the M&S community are rapidly changing, both in terms of the nations that use M&S and the academic disciplines from which new simulationists hail. This change in demographics has the potential to help aid the community face some of its future challenges. Our qualitative literature review indicates that DES still faces some significant challenges: these include integrating human behavior; using simulation for exploration, not replication; determining return on investment; and communication issues across a splitting community.

show abstract

A history of simulation development in the United Kingdom

Cited by 4 publications

References 25 publications

Historical and Philosophical Perspectives on the Activity of Modelling

Historical and Philosophical Perspectives on the Activity of Modelling

Proceedings of SW21 The OR Society Simulation Workshop

Past challenges and the future of discrete event simulation

Contact Info

Product

Resources

About