Title
Comparing conventional and distributed approaches to simulation in a complex supply-chain health system
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.
Year
DOI
Venue
2009
10.1057/palgrave.jors.2602531
JORS
Keywords
Field
DocType
supply chain,communications technology,operations research,computer science,operational research,production,reliability,location,information technology,information systems,scheduling,investment,forecasting,inventory,management science,project management,marketing,logistics
Information system,Simulation software,Distributed element model,Scheduling (computing),Computer science,Decision support system,Supply chain,Operations management,Project management
Journal
Volume
Issue
ISSN
60
1
0160-5682
Citations 
PageRank 
References 
4
0.44
12
Authors
4
Name
Order
Citations
PageRank
Korina Katsaliaki113411.91
Navonil Mustafee237844.76
S. J.E. Taylor355167.71
Sally C. Brailsford439735.84