Simulation Optimisation for Improving the Efficiency of a Production Line

Calverley, Joseph; Currie, Christine S. M.; Onggo, Bhakti Stephan; Monks, Thomas; Higgins, Michael J.

doi:10.36819/sw21.014

Cited by 4 publications

(2 citation statements)

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“…Monks (2021) provides a general Python implementation of OCBA which is used in our computational experiments. We refer the interested reader to Calverley et al (2021) and Currie and Monks (2021) for more details about OCBA.…”

Section: Ocba Algorithmmentioning

confidence: 99%

Location of chief police officers in the state of Pernambuco, Brazil, using OCBA

Wei¹,

Lamas-Fernandez²,

Coutinho³

et al. 2023

Proceedings of SW21 the OR Society Simulation Workshop

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Section: Ocba Algorithmmentioning

confidence: 99%

Location of chief police officers in the state of Pernambuco, Brazil, using OCBA

Wei¹,

Lamas-Fernandez²,

Coutinho³

et al. 2023

Proceedings of SW21 the OR Society Simulation Workshop

View full text Add to dashboard Cite

Section: Ocba Algorithmmentioning

confidence: 99%

Proceedings of SW21 The OR Society Simulation Workshop

2023

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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.

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Real-time digital twin-based optimization with predictive simulation learning

Goodwin

Celik

et al. 2022

Journal of Simulation

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Simulation Optimisation for Improving the Efficiency of a Production Line

Cited by 4 publications

References 0 publications

Location of chief police officers in the state of Pernambuco, Brazil, using OCBA

Location of chief police officers in the state of Pernambuco, Brazil, using OCBA

Proceedings of SW21 The OR Society Simulation Workshop

Real-time digital twin-based optimization with predictive simulation learning

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