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

Serious games for sustainable development

Sustainable development (SD) is the development that meets the needs of the present without compromising the ability of the subsequent generations to cater to their future needs (Brundtland, 1987). An ecologically balanced environment, long-term economic well-being, and social equity are commonly regarded as the triple bottom line (TBL) of SD. Effective management of the TBL requires the adoption of SD practices (Pope, Annandale, & Morrison- Saunders, 2004). The concepts of SD and the TBL have emerged as a major focus for the society because of factors such as the depletion of natural resources, changes in demographics, and a push toward a more equitable society. To achieve the goals of TBL, we will need the right attitude and managerial skills to examine these challenges holistically (Savitz, 2006), and the adoption of courses and degrees focusing on SD will play an important role in the curriculum of intermediate and higher education (Cotton, Warren, Maiboroda, & Bailey, 2007). The focus of this review is the use of serious games (SGs), designed with a primary purpose other than pure entertainment, as a tool to teach SD

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

Exploring the modelling and simulation knowledge base through journal co-citation analysis

“The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-013-1136-zCo-citation analysis is a form of content analysis that can be applied in the context of scholarly publications with the purpose of identifying prominent articles, authors and journals being referenced to by the citing authors. It identifies co-cited references that occur in the reference list of two or more citing articles, with the resultant co-citation network providing insights into the constituents of a knowledge domain (e.g., significant authors and papers). The contribution of the paper is twofold; (a) the demonstration of the added value of using co-citation analysis, and for this purpose the underlying dataset that is chosen is the peer-reviewed publication of the Society for Modeling and Simulation International (SCS)—SIMULATION; (b) the year 2012 being the 60th anniversary of the SCS, the authors hope that this paper will lead to further acknowledgement and appreciation of the Society in charting the growth of Modeling and Simulation (M&S) as a discipline

A game-based approach towards facilitating decision making for perishable products: an example of blood supply chain

NOTICE: this is the author’s version of a work that was accepted for publication in Expert Systems with Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications, Volume 41, Issue 9, July 2014, Pages 4043–4059 doi:10.1016/j.eswa.2013.12.038Supply chains for perishable items consist of products with a fixed shelf life and limited production/collection; managing them requires competent decision-making. With the objective of placing the learners in the position of decision-makers, we propose the Blood Supply Chain Game which simulates the supply chain of blood units from donors to patients based on a real case study modeling the UK blood supply chain. The Excel-based game is an abstraction of the technical complex simulation model providing a more appropriate learning environment. This paper presents the game’s background, its mathematical formulations, example teaching scenarios and the learners’ evaluation. The game aims to translate qualitative aspects of a sensitive supply chain into quantitative economic consequences by presenting a process analysis and suggesting solutions for the patient’s benefit in a cost effective manner, trying to synchronize blood demand and supply and maximize the value of the whole supply chain. This innovative approach will be instructive for students and healthcare service professionals

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

SCS: 60 years and counting! A time to reflect on the Society's scholarly contribution to M&S from the turn of the millennium.

The Society for Modeling and Simulation International (SCS) is celebrating its 60th anniversary this year. Since its inception, the Society has widely disseminated the advancements in the field of modeling and simulation (M&S) through its peer-reviewed journals. In this paper we profile research that has been published in the journal SIMULATION: Transactions of the Society for Modeling and Simulation International from the turn of the millennium to 2010; the objective is to acknowledge the contribution of the authors and their seminal research papers, their respective universities/departments and the geographical diversity of the authors' affiliations. Yet another objective is to contribute towards the understanding of the overall evolution of the discipline of M&S; this is achieved through the classification of M&S techniques and its frequency of use, analysis of the sectors that have seen the predomination application of M&S and the context of its application. It is expected that this paper will lead to further appreciation of the contribution of the Society in influencing the growth of M&S as a discipline and, indeed, in steering its future direction

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