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


Katsaliaki, K., Mustafee, N., Taylor, S.J.E. and Brailsford, S. (2007) Comparing conventional and distributed approaches to simulation in a complex supply-chain health system. Journal of the Operational Research Society, 9pp. (doi:10.1057/palgrave.jors.2602531).

Download

Full text not available from this repository.

Description/Abstract

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.

Item Type: Article
ISSNs: 0160-5682 (print)
Related URLs:
Keywords: distributed simulation, supply chain systems, healthcare operations, simulation software, simul8
Subjects: R Medicine > R Medicine (General)
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Q Science > QA Mathematics > QA76 Computer software
Divisions: University Structure - Pre August 2011 > School of Management
ePrint ID: 51317
Date Deposited: 06 Jun 2008
Last Modified: 27 Mar 2014 18:34
Contact Email Address: S.C.Brailsford@soton.ac.uk
URI: http://eprints.soton.ac.uk/id/eprint/51317

Actions (login required)

View Item View Item