Modelling very large complex systems using distributed simulation: A pilot study in a healthcare setting

Modern manufacturing supply chains are hugely complex and like all stochastic systems, can benefit from simulation. Unfortunately supply chain systems often result in massively large and complicated models, which even today’s powerful computers cannot run efficiently. This paper presents one possible solution - distributed simulation. This pilot study is implemented in a healthcare setting, the supply chain of blood from donor to recipient

Methodology for profiling literature in healthcare simulation

The publications that relate to the application of simulation to healthcare have steadily increased over the years. These publications are scattered amongst various journals that belong to several subject categories, including Operational Research, Health Economics and Pharmacokinetics. The simulation techniques that are applied to the study of healthcare problems are also varied. The aim of this study is to present a methodology for profiling literature in healthcare simulation. In our methodology, we have considered papers on healthcare that have been published between 1970 and 2007 in journals with impact factors that belonging to various subject categories reporting on the application of four simulation techniques, namely, Monte Carlo Simulation, Discrete-Event Simulation, System Dynamics and Agent-Based Simulation. The methodology has the following objectives: (a) to categorise the papers under the different simulation techniques and identify the healthcare problems that each technique is employed to investigate; (b) to profile, within our dataset, variables such as authors, article citations, etc.; (c) to identify turning point (strategically important) papers and authors through co-citation analysis of references cited by the papers in our dataset. The focus of the paper is on the literature profiling methodology, and not the results that have been derived through the application of this methodology. The authors hope that the methodology presented here will be used to conduct similar work in not only healthcare but also other research domains

Comparing conventional and distributed approaches to simulation in complex supply-chain health systems

Decision making in modern supply chains can be extremely daunting due to their complex nature. Discrete-event simulation is a technique that can support decision making by providing what-if analysis and evaluation of quantitative data. However, modelling supply chain systems can result in massively large and complicated models that can take a very long time to run even with today's powerful desktop computers. Distributed simulation has been suggested as a possible solution to this problem, by enabling the use of multiple computers to run models. To investigate this claim, this paper presents experiences in implementing a simulation model with a 'conventional' approach and with a distributed approach. This study takes place in a healthcare setting, the supply chain of blood from donor to recipient. The study compares conventional and distributed model execution times of a supply chain model simulated in the simulation package Simul8. The results show that the execution time of the conventional approach increases almost linearly with the size of the system and also the simulation run period. However, the distributed approach to this problem follows a more linear distribution of the execution time in terms of system size and run time and appears to offer a practical alternative. On the basis of this, the paper concludes that distributed simulation can be successfully applied in certain situations

Distributed simulation with COTS simulation packages: A case study in health care supply chain simulation

The UK National Blood Service (NBS) is a public funded body that is responsible for distributing blood and asso-ciated products. A discrete-event simulation of the NBS supply chain in the Southampton area has been built using the commercial off-the-shelf simulation package (CSP) Simul8. This models the relationship in the health care supply chain between the NBS Processing, Testing and Is-suing (PTI) facility and its associated hospitals. However, as the number of hospitals increase simulation run time be-comes inconveniently large. Using distributed simulation to try to solve this problem, researchers have used techniques informed by SISO’s CSPI PDG to create a version of Simul8 compatible with the High Level Architecture (HLA). The NBS supply chain model was subsequently divided into several sub-models, each running in its own copy of Simul8. Experimentation shows that this distri-buted version performs better than its standalone, conven-tional counterpart as the number of hospitals increases

Using CSPI distributed simulation standards for the analysis of a health supply chain

COTS Simulation Package Interoperability is a problem that has been studied by the Simulation Interoperability Standards Organization’s (SISO) COTS Simulation Package Interoperability Product Development Group (CSPI PDG). The UK National Blood Service maintains the supply chain of blood from donor to hospital. The simulation of this supply chain is vital to better support decisons made for an extremely scarce resource. Such models are very large and can take a very long time to execute. This paper investigates whether or not CSPI PDG standards can be used to create a distributed simulation of this supply chain and if a speed up can be achieved. The results show that for larger blood supply chain models this is the case

Classification of the Existing Knowledge Base of OR/MS Research and Practice (1990-2019) using a Proposed Classification Scheme

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordOperations Research/Management Science (OR/MS) has traditionally been defined as the discipline that applies advanced analytical methods to help make better and more informed decisions. The purpose of this paper is to present an analysis of the existing knowledge base of OR/MS research and practice using a proposed keywords-based approach. A conceptual structure is necessary in order to place in context the findings of our keyword analysis. Towards this we first present a classification scheme that relies on keywords that appeared in articles published in important OR/MS journals from 1990-2019 (over 82,000 articles). Our classification scheme applies a methodological approach towards keyword selection and its systematic classification, wherein approximately 1300 most frequently used keywords (in terms of cumulative percentage, these keywords and their derivations account for more than 45% of the approx. 290,000 keyword occurrences used by the authors to represent the content of their articles) were selected and organised in a classification scheme with seven top-level categories and multiple levels of sub-categories. The scheme identified the most commonly used keywords relating to OR/MS problems, modeling techniques and applications. Next, we use this proposed scheme to present an analysis of the last 30 years, in three distinct time periods, to show the changes in OR/MS literature. The contribution of the paper is thus twofold, (a) the development of a proposed discipline-based classification of keywords (like the ACM Computer Classification System and the AMS Mathematics Subject Classification), and (b) an analysis of OR/MS research and practice using the proposed classification

Distributed Approaches to Supply Chain Simulation: A Review

This is the author accepted manuscript. The final version is available from ACM via the DOI in this recordThe field of Supply Chain Management (SCM) is experiencing rapid strides in the use of Industry 4.0 technologies and the conceptualization of new supply chain configurations for online retail, sustainable and green supply chains and the Circular Economy. Thus, there is an increasing impetus to use simulation techniques such as discrete-event simulation, agent-based simulation and hybrid simulation in the context of SCM. In conventional supply chain simulation, the underlying constituents of the system like manufacturing, distribution, retail and logistics processes are often modelled and executed as a single model. Unlike this conventional approach, a distributed supply chain simulation (DSCS) enables the coordinated execution of simulation models using specialist software. To understand the current state-of-the-art of DSCS, this paper presents a methodological review and categorization of literature in DSCS using a framework-based approach. Through a study of over 130 articles, we report on the motivation for using DSCS, the modelling techniques, the underlying distributed computing technologies and middleware, its advantages and a future agenda, as also limitations and trade-offs that may be associated with this approach. The increasing adoption of technologies like Internet-of-Things and Cloud Computing will ensure the availability of both data and models for distributed decision-making, and which is likely to enable data-driven DSCS of the future. This review aims to inform organizational stakeholders, simulation researchers and practitioners, distributed systems developers and software vendors, as to the current state of the art of DSCS, and which will inform the development of future DSCS using new applied computing approaches

Applications of simulation within the healthcare context

This is a pre-print of an article published in Journal of the Operation Research Society. The definitive publisher-authenticated version Katsaliaki, K., Mustafee, N.,(2010). Applications of simulation within the healthcare context. Journal of the Operation Research Society. 62, 1431-1451 is available online at: http://www.palgrave-journals.com/jors/journal/v62/n8/full/jors201020a.htmlA large number of studies have applied simulation to a multitude of issues related to healthcare. These studies have been published over a number of unrelated publishing outlets, and this may hamper the widespread reference and use of such resources. In this paper we analyse existing research in healthcare simulation in order to categorise and synthesise it in a meaningful manner. Hence, the aim of this paper is to conduct a review of the literature pertaining to simulation research within healthcare in order to ascertain its current development. A review of approximately 250 high quality journal papers published between 1970 and 2007 on healthcare-related simulation research was conducted. The results present: a classification of the healthcare publications according to the simulation techniques they employ; the impact of published literature in healthcare simulation; a report on demonstration and implementation of the studies’ results; the sources of funding; and the software used. Healthcare planners and researchers will benefit from this study by having ready access to an indicative article collection of simulation techniques applied in healthcare problems that are clustered under meaningful headings. This study facilitates the understanding of the potential of different simulation techniques for solving diverse healthcare problems

Portable optical blood scattering sensor

Modern non-invasive medical sensors can continuously provide vital information such as blood oxygenation, hemoglobin and glucose, based on substance-specific spectral or electrochemical properties. Cells and other geometrical formations are difficult to observe non-invasively due to the absence of a distinctive substantial signature. Optical scattering angle measurements could provide geometrical information but multiple scattering results in diffusion profiles, limiting their direct applicability. Mie scattering correlation to blood cell size has been demonstrated in the lab and various biomedical optical techniques are under intense investigation towards decoupling direct from indirect scattering, requiring specialized equipment. In this paper, a portable sensor is introduced for in-vitro and potentially in-vivo study of light scattering from blood. A microcontroller-based prototype has been designed and fabricated, with a 650 nm laser source, a 128 × 1 photodiode array and a custom dual-core real-time data acquisition algorithm. The prototype has been evaluated using latex sphere solutions calibrated to emulated red blood cells, white blood cells and platelets. Distinct scattering signatures are demonstrated for the three blood cell sizes. Reproducibility and repeatability tests analyzing data from multiple independent experiments demonstrate the reliability of the demonstration. This device platform provides a flexible and simple means for evaluating optical processing methods towards non-invasive continuous counting of blood cells

Simulation methods in the healthcare systems

International audienceHealthcare systems can be considered as large-scale complex systems. They need to be well managed in order to create the desired values for its stakeholders as the patients, the medical staff and the industrials working for healthcare. Many simulation methods coming from other sectors have already proved their added value for healthcare. However, based on our experience in the French heath sector (Jean et al. 2012), we found these methods are not widely used in comparison with other areas as manufacturing and logistic. This paper presents a literature review of the healthcare issue and major simulations methods used to address them. This work is design to suggest how more systematic creation of solutions may be performed using complementary methods to resolve a common issue. We believe that this first work can help to better understand the simulation approaches used for health workers, deciders or researchers of any responsibility level