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On the performance of inter-organizational design optimization systems
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Source Winter Simulation Conference archive
Proceedings of the 38th conference on Winter simulation table of contents
Monterey, California
SESSION: Modeling methodology b: modeling of distributed systems table of contents
Pages: 1177 - 1186  
Year of Publication: 2006
ISBN:1-4244-0501-7
Authors
Paolo Vercesi  ESTECO, Trieste, TS, ITALY
Alberto Bartoli  University of Trieste, Trieste, TS, ITALY
Sponsors
IEICE ESS : Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
IIE : Institute of Industrial Engineers
ASA : American Statistical Association
IEEE-CS\DATC : The IEEE Computer Society
INFORMS-CS : Institute for Operations Research and the Management Sciences-College on Simulation
NIST : National Institute of Standards and Technology
SIGSIM: ACM Special Interest Group on Simulation and Modeling
(SCS) : The Society for Modeling and Simulation International
Publisher
Winter Simulation Conference 
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ABSTRACT

Simulation-based design optimization is a key technology in many industrial sectors. Recent developments in software technology have opened a novel range of possibilities in this area. It has now become possible to involve multiple organizations in the simulation of a candidate design, by composing their respective simulation modules on the Internet. Thus, it is possible to deploy an inter-organizational design optimization system, which may be particularly appealing because modern engineering products are assembled out of smaller blocks developed by different organizations. In this paper we explore some of the fundamental performancerelated issues involved in such a novel scenario, by analyzing a variety of options: centralized control vs. distributed control; generation of new candidate designs one at a time or in batches; communication and computation performed serially or with time overlap. Our analysis provides useful insights into the numerous trade-offs involved in the implementation of inter-organizational design optimization.


REFERENCES

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Collaborative Colleagues:
Paolo Vercesi: colleagues
Alberto Bartoli: colleagues