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

Katsaliaki, Korina, Mustafee, N., Taylor, S. J. E. and Brailsford, Sally C. (2009) Comparing conventional and distributed approaches to simulation in a complex supply-chain health system. Journal of the Operational Research Society, 60 (1) . pp. 43-51. ISSN 0160-5682 [Article] (doi:10.1057/palgrave.jors.2602531)


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
Research Areas: A. > Business School > Economics
ISI Impact: 1
Item ID: 661
Depositing User: Repository team
Date Deposited: 04 Dec 2008 13:30
Last Modified: 13 Oct 2016 14:12

Actions (login required)

View Item View Item


Activity Overview
6 month trend
6 month trend

Additional statistics are available via IRStats2.