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

This study develops a standardised checklist approach to improve the reporting of discrete-event simulation, system dynamics and agent-based simulation models within the field of Operational Research and Management Science. Incomplete or ambiguous reporting means that many simulation studies are not reproducible, leaving other modellers with an incomplete picture of what has been done and unable to judge the reliability of the results. Crucially, unclear reporting makes it difficult to reproduce or reuse findings. In this paper, we review the evidence on the quality of model reporting and consolidate previous work. We derive general good practice principles and three 20-item checklists aimed at Strengthening The Reporting of Empirical Simulation Studies (STRESS): STRESS-DES, STRESS-ABS and STRESS-SD for discrete-event simulation, agentbased simulation and system dynamics, respectively. Given the variety of simulation projects, we provide usage and troubleshooting advice to cover a wide range of situations.

Agri-food supply chains (ASC) are an important application domain for Operational Research/Management Science. In particular, the use of agent-based simulation (ABS) has increased in ASC research in recent years. This paper reviews existing ASC research that use ABS. The review begins by analysing the characteristics of the models and modelling reported in the literature. It illustrates that existing modelling research features extensive use of: single echelon supply chains; cases from high and middle income countries; unprocessed food products, empirical (as opposed to hypothetical) data; decision-making related to production planning and investment; and the use of black box validation. The second part of the review uses bibliographic mapping to analyse areas in ASC research which are yet to be addressed using ABS. We find that areas such as collaboration and competition, buyer-seller relationships, and service are underresearched. In addition, key actors in ASC such as food processors, supermarkets and retailers have not been included in the ABS models reported. Furthermore, these models have yet to incorporate important supply chain management theories such as Transaction Cost Economics and Resource-Based View as part of their design.

Hybrid simulation comes in many shapes and forms. It has been argued by many researchers that hybrid simulation provides a better insight of the system in hand as it allows modelers to assess its inherent problems from different dimensions. As a result Hybrid Simulation is becoming an important field within the Modeling and Simulation arena. Yet we find that there no clear and cohesive definition for it. Therefore, this panel paper aims to explore the concept of Hybrid Simulation and its progression through the years. In doing so, we hope to lay out the underpinnings of a structured Hybrid Simulation approach by providing historical narratives of the origins of hybrid models; the current challenges expressed by scholars; and future studies to ensure more focused development of a comprehensive methodology for Hybrid Simulation.

This paper considers an agri-food supply chain with a single fresh food supplier, who owns a central warehouse that serves several retail centers. Retail centers carry a certain amount of inventory of the fresh product, which is prone to deterioration. The supplier makes both inventory and routing decisions to minimize the inventory, transportation, food-waste, and stock-out costs in the face of stochastic customer demand and perishable products that need to be delivered to each retail center. This inventory routing problem is known as perishable inventory routing problem (PIRP) with stochastic demands in the literature. We model it using a mixed integer program and propose a simheuristic algorithm, which integrates Monte Carlo simulation within an iterated local search, to solve it. Our experiments show that the proposed algorithm can improve the initial solution with reasonable computational times. The resulting procedure is easy to implement and is applicable to other domains where a multi-period PIRP with stochastic demands may appear.

Phone: +44 (0)161 306 3429 [Blue text indicates changes]EJOR RR3 Paper 4.16.docx 2 AbstractThe 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.

Stakeholder engagement in simulation projects is important, especially in healthcare where there is a plurality of stakeholder opinions, objectives and power. One promising approach for increasing engagement is facilitated modelling. Currently, the complexity of producing a simulation model means that the 'model coding' stage is performed without the involvement of stakeholders, interrupting the possibility of a fully-facilitated project. Early work demonstrated that with currently-available software tools we can represent a simple healthcare process using Business Process Model and Notation (BPMN) and generate a simulation model automatically. However, for more complex processes, BPMN currently has a number of limitations, namely the ability to represent queues and data-driven decision points. To address these limitations, we propose a conceptual design for an extension to BPMN (BPMN4SIM) using Model Driven Architecture. Application to an elderly emergency care pathway in a UK hospital shows that BPMN4SIM is able to represent a more-complex business process.

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