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Simulation Modelling Practice and Theory 12 (2004) 475–477

Preface

Stewart Robinson a,1, Simon J.E. Taylor b,2

a Warwick Business School, University of Warwick, Coventry CV4 7AL, UKb Department of Information Systems and Computing, Brunel University, Uxbridge,

Middlesex UB8 3PH, UK

Available online 25 August 2004

This special issue of Simulation Modelling Practice and Theory focuses on the use

of simulation in operational research. The simulation approach that is primarilyused within this context is discrete-event simulation. This is reflected in the papers

that follow. Among the operational research community there is also a growing

interest in the use of other simulation methods, especially system dynamics and agent

based simulation. This too is reflected in the selection of papers in this issue (see

Alam et al., and Moffat and Passman).

All the articles were originally presented at the Operational Research Society�sbiennial Simulation Workshop (SW02) held in Birmingham in March 2002 [1].

This event attracted practitioners and researchers from across the UK and furtherafield. Attended by more than 60 delegates, the papers represented the range

of simulation research and practice in the operational research community.

Some of those papers have been revised and expanded for inclusion in this special

issue.

Apart from the formal papers that were presented at the workshop, there was a

lively panel discussion on the issue of simulation model reuse. This is something

of a hot topic within the operational research and wider simulation community,

especially with the growing use of the internet. The panel members Professor Ri-chard Nance, Professor Ray Paul, Professor Michael Pidd and Dr. Simon Taylor ex-

pressed various opinions about the definition, possibilities and problems of model

1569-190X/$ - see front matter � 2004 Elsevier B.V. All rights reserved.

doi:10.1016/j.simpat.2004.07.001

1 E-mail address: stewart.robinson@warwick.ac.uk2 E-mail address: simon.taylor@brunel.ac.uk

476 S. Robinson, S.J.E. Taylor / Simulation Modelling Practice and Theory 12 (2004) 475–477

reuse. Following the workshop, this discussion has been written-up and provides the

first paper in this issue.

Following on from this, Oses et al. discuss the issues involved in the develop-

ment of component-based discrete simulations. They argue that many of the

technical problems in developing component-based simulations have been solved,

but that there are various practical issues that need to be addressed for it to be-

come viable. They also point out that simulation software is quite different fromgeneral software and, therefore, the requirements for components are quite

different.

The next two papers focus on the inclusion of the human element in simulation

models. Baines et al. argue that simulation accuracy can be increased by including

the effects of human variation. To illustrate this they add age effects and circadian

rhythm effects to a model of a Ford manufacturing plant. In doing so they demon-

strate the difference in the performance of the system being modelled. As part of an

ongoing research programme, Baines et al. intend to develop valid models for pro-duction line workers. Meanwhile, Edwards et al. discuss the use of simulation for

eliciting knowledge from decision-makers and as a basis for supporting knowledge

management in an organisation. Simulation is seen as a means for acquiring, sharing

and refining knowledge. These ideas have also been tested in a Ford manufacturing

plant.

Moving away from the manufacturing domain, the paper by Baldwin et al. dis-

cusses the use of simulation in healthcare management. Simulation is used in an eval-

uation of liver transplant technology. The main argument of the paper involves theproposal for an alternative, softer, methodology for developing and using simula-

tions. The aim is provide a participative approach to simulation modelling whose

prime aim is to enhance understanding and communication among the problem

owners.

Simulation and metamodelling have been discussed by the operational research

community for some time. In this issue two papers focus on the use of metamodel-

ling, both within the military domain. Alam et al. investigate the use of alternative

experimental design methods in developing neural network based metamodels.Based on a system dynamics model of combat they test various experimental design

methods, concluding that traditional designs are appropriate for relatively smooth

response surfaces, but that other approaches are needed for more complex surfaces.

Moffat and Passman develop a causally based metamodel of a complex (agent-based)

simulation of conflict. The metamodel provides useful insights into the emergent

behaviour of the system. They argue that the approach could be transferred to

any simulation that involves complex interactions similar to those found in fluid

dynamics.The final paper, Karatza, investigates four scheduling strategies for distributed

server systems. A key feature of this work is that it involves time varying distribu-

tions for job inter-arrival time, number of tasks per job and task service demand.

The results of experimentation show that the shortest-task-first strategy performs

best, although all the strategies investigated have merit.

S. Robinson, S.J.E. Taylor / Simulation Modelling Practice and Theory 12 (2004) 475–477 477

These papers reflect a range of applications, technologies and simulation ap-

proaches as they are applied in operational research. It is hoped that this issue of

Simulation Modelling Practice and Theory provides the reader with a useful snap-

shot of the work being carried out by this community.

Reference

[1] T. Eldabi, S. Robinson, S.J.E. Taylor, P.A. Wilcox, in: Proceedings of the Operational Research

Society Simulation Workshop (SW02), Operational Research Society, Birmingham, UK, 2002.