Editorial: 10^th Anniversary post-simulation workshop 2021 special issue

This JOS special issue showcases a selection of specially curated papers from the pool of proceedings papers presented at the biennial UK OR Society 2021 Simulation Workshop (SW21). It marks the 10^th anniversary milestone in celebration of the Simulation Workshop, after 20 years of the conference series, with the first one running in 2002.

The conference was originally planned to be held in March 2020 but was postponed by a year and moved to an online format due to the COVID-19 pandemic. Even though the COVID pandemic had an impact on the conference, it did not affect the quality of the programme. SW21 offered the delegates an update on the latest developments in the simulation field as well as a unique opportunity to network and collaborate over a five-day period. It was not coincidental that delegate feedback recognised SW21 as the best online conference they had attended. The conference programme included all the successful features of previous conferences, while it saw the inclusion of new features which aimed to enhance the virtual conference experience, such as a hackathon-style modelling competition, online networking sessions (wellbeing- and sport- themed and roundtable discussions on topical simulation issues), an Equity, Diversity and Inclusivity (EDI) session to celebrate Professor Sally Brailsford’s lifetime achievements in the simulation and healthcare modelling field, and more. For further details about the conference, please refer to Anagnostou and Tako (2021).

SW21 celebrated the latest simulation and modelling research and its application to practice. The conference proceedings included 35 contributed papers on a range of simulation topics, including COVID-19 simulation, artificial intelligence, conceptual modelling, crowd control and data farming. This special issue presents a selection of eight articles that were curated and significantly extended from the original proceedings’ papers. Each paper included in this special issue (SI) has undergone a rigorous review process, ensuring that it meets the journal’s high standards of quality and relevance.

While some papers are on application-specific topics such as the spread of infectious diseases, health and care services, financial problems, and farming, other papers in the special issue focus on practical aspects related to simulation modelling methodology, such as the use of “wrong” simulation models (Tsioptsias et al., 2022) or the development of conceptual models using machine learning (Abuhay et al., 2023). The papers showcase a variety of simulation methodologies, including simulation optimisation (Nieto et al., 2022), system dynamics (Herrera & Kopainsky, 2022; Linnéusson & Goienetxea Uriarte, 2023), discrete-event simulation (Abuhay et al., 2023), and even a mix of simulation methods and broader Operational Research methods such as Soft Systems Methodology (Conlon & Molloy, 2023).

Next, we provide a brief summary of the papers included in the 10^th Anniversary post-Simulation Workshop 2021 special issue.

The first paper of this special issue, titled “Celebrating the 10^th Simulation Workshop: The story of the conference series”, is written by the founders of the Simulation Workshop (Robinson & Taylor, 2022). The authors provide a short history of the conference series, including the events that led up to the first conference, details of the first Simulation Workshop and a summary of the other nine workshops that took place subsequently.

The paper by Cheng et al. (2023) “Modelling pre-symptomatic Infectiousness in COVID-19” focuses on the topical issue of modelling infectious diseases. The authors develop an extension of the well-known SEIR (susceptible, exposed, infectious, and recovered) continuous simulation model to include an additional pre-symptomatic infectious compartment. Their simulation model thus includes five compartments and is referred to as SEPIR. It focuses on modelling the first wave of the spread of the COVID epidemic. The authors consider how reproduction numbers can be calculated to investigate an epidemic’s longer-term overall result.

The SI continues with the theme of healthcare modelling with the next three articles. The paper titled “Modelling a computed tomography service using mixed operational research methods” investigates resource utilisation and increasing waiting lists for a Computed Tomography (CT) scanning service (Conlon & Molloy, 2023). The authors adopt a facilitated modelling approach and use a combination of OR techniques (System Dynamics, Soft Systems Methodology and Discrete Event Simulation) to model the CT service. The study concludes that to address the problem of growing CT waiting lists, the separation of inpatient and outpatient CT scanning services is recommended.

The paper “Learning from simulating with system dynamics in healthcare: “Evaluating closer care strategies for elderly patients” presents a case study that aims to improve care services for elderly patients in a regional healthcare system in Sweden (Linnéusson & Goienetxea Uriarte, 2023). The authors use system dynamics modelling to investigate the impact of proactive care policies, whereby services are offered closer to the patient in the community (e.g., primary care, home care) and how this can help reduce elderly patients’ attendance at the emergency department and subsequent hospitalisations as well as their hospital length of stay. The study discusses the importance of stakeholder involvement and benefits of using system dynamics to understand the dynamics of elderly patients in the healthcare system.

The paper by Abuhay et al. (2023) is on “Machine learning-integrated patient flow simulation: Why and how?”. The authors describe why coupling machine learning with patient flow simulation is important and propose a conceptual model for constructing machine learning-integrated patient flow simulations. The proposed architecture aims to increase the credibility and acceptance of patient flow simulation models by reducing uncertainties and improving the accuracy of patient flow simulation models. The authors provide a proof of concept by demonstrating its implementation with examples.

The paper titled “Are ‘wrong’ models useful?: A qualitative study of discrete-event simulation modeller stories” (Tsioptsias et al., 2022) presents a qualitative text analysis of 54 modellers stories reporting about models considered to be “wrong” either by the modeller, the client or both. The aim of the study is to improve the understanding of “wrong” discrete-event simulation models empirically. Their findings show that even though some models which may be considered “wrong” may still be useful in practice and can provide valuable insights to users and modellers. The paper offers practical suggestions on potential uses of “wrong” models to users and modellers.

In “Using microworlds for policymaking in the context of resilient farming systems” (Herrera & Kopainsky, 2022), the authors use an interactive simulation model to explore the conditions for a scenario that finds a compromise between environmental and socioeconomic goals with the aim of finding sustainable futures for meat producers in Europe. The results of the study offer insights into the potential trade-offs between systems scale and long-term sustainability by suggesting that sacrificing socioeconomic performance in the short and medium term may increase long-term sustainability and resilience.

The paper by Nieto et al. (2022) “A GA-Simheuristic for the stochastic and multi-period portfolio optimisation problem with liabilities” demonstrates the use of simulation and a genetic algorithm (GA) in financial optimisation problems under uncertainty. The paper aims to define the portfolio of assets to be kept at each period so that the terminal wealth is maximised while satisfying all liabilities in due time. To achieve this, the authors propose an approach that integrates Monte Carlo simulation at different stages of a GA to analyse a stochastic and multi-period asset-liability problem. The proposed GA-simheuristic approach constitutes an effective methodology for solving complex financial problems that require the matching of assets and exogenous cash-flows.

We thank the authors for submitting extended versions of their work presented at SW21. We appreciate their dedication to and engagement with the JOS peer review process. We also appreciate the reviewers’ constructive comments and invaluable suggestions that have helped enhance the quality of the papers. Furthermore, we thank the JOS Editors for their unwavering support and assistance in preparing this special issue. We hope you find the papers in this special issue informative and interesting!

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.