Finding the Important Factors in Large Discrete-Event Simulation

Sequential Bifurcation and its Applications

J.P.C. Kleijnen, B.W.M. Bettonvil, F. Persson

Research output: Working paperDiscussion paperOther research output

276 Downloads (Pure)

Abstract

This contribution discusses experiments with many factors: the case study includes a simulation model with 92 factors.The experiments are guided by sequential bifurcation.This method is most efficient and effective if the true input/output behavior of the simulation model can be approximated through a first-order polynomial possibly augmented with two-factor interactions.The method is explained and illustrated through three related discrete-event simulation models.These models represent three supply chain configurations, studied for an Ericsson factory in Sweden.After simulating 21 scenarios (factor combinations) each replicated five times to account for noise a shortlist with the 11 most important factors is identified for the biggest of the three simulation models.
Original languageEnglish
Place of PublicationTilburg
PublisherOperations research
Number of pages29
Volume2003-104
Publication statusPublished - 2003

Publication series

NameCentER Discussion Paper
Volume2003-104

Fingerprint

Discrete event simulation
Supply chains
Industrial plants
Experiments
Polynomials

Keywords

  • simulation
  • bifurcation
  • supply
  • Sweden

Cite this

Kleijnen, J. P. C., Bettonvil, B. W. M., & Persson, F. (2003). Finding the Important Factors in Large Discrete-Event Simulation: Sequential Bifurcation and its Applications. (CentER Discussion Paper; Vol. 2003-104). Tilburg: Operations research.
Kleijnen, J.P.C. ; Bettonvil, B.W.M. ; Persson, F. / Finding the Important Factors in Large Discrete-Event Simulation : Sequential Bifurcation and its Applications. Tilburg : Operations research, 2003. (CentER Discussion Paper).
@techreport{277fbeadf29b4deea74dc1093f42aac1,
title = "Finding the Important Factors in Large Discrete-Event Simulation: Sequential Bifurcation and its Applications",
abstract = "This contribution discusses experiments with many factors: the case study includes a simulation model with 92 factors.The experiments are guided by sequential bifurcation.This method is most efficient and effective if the true input/output behavior of the simulation model can be approximated through a first-order polynomial possibly augmented with two-factor interactions.The method is explained and illustrated through three related discrete-event simulation models.These models represent three supply chain configurations, studied for an Ericsson factory in Sweden.After simulating 21 scenarios (factor combinations) each replicated five times to account for noise a shortlist with the 11 most important factors is identified for the biggest of the three simulation models.",
keywords = "simulation, bifurcation, supply, Sweden",
author = "J.P.C. Kleijnen and B.W.M. Bettonvil and F. Persson",
note = "Pagination: 29",
year = "2003",
language = "English",
volume = "2003-104",
series = "CentER Discussion Paper",
publisher = "Operations research",
type = "WorkingPaper",
institution = "Operations research",

}

Kleijnen, JPC, Bettonvil, BWM & Persson, F 2003 'Finding the Important Factors in Large Discrete-Event Simulation: Sequential Bifurcation and its Applications' CentER Discussion Paper, vol. 2003-104, Operations research, Tilburg.

Finding the Important Factors in Large Discrete-Event Simulation : Sequential Bifurcation and its Applications. / Kleijnen, J.P.C.; Bettonvil, B.W.M.; Persson, F.

Tilburg : Operations research, 2003. (CentER Discussion Paper; Vol. 2003-104).

Research output: Working paperDiscussion paperOther research output

TY - UNPB

T1 - Finding the Important Factors in Large Discrete-Event Simulation

T2 - Sequential Bifurcation and its Applications

AU - Kleijnen, J.P.C.

AU - Bettonvil, B.W.M.

AU - Persson, F.

N1 - Pagination: 29

PY - 2003

Y1 - 2003

N2 - This contribution discusses experiments with many factors: the case study includes a simulation model with 92 factors.The experiments are guided by sequential bifurcation.This method is most efficient and effective if the true input/output behavior of the simulation model can be approximated through a first-order polynomial possibly augmented with two-factor interactions.The method is explained and illustrated through three related discrete-event simulation models.These models represent three supply chain configurations, studied for an Ericsson factory in Sweden.After simulating 21 scenarios (factor combinations) each replicated five times to account for noise a shortlist with the 11 most important factors is identified for the biggest of the three simulation models.

AB - This contribution discusses experiments with many factors: the case study includes a simulation model with 92 factors.The experiments are guided by sequential bifurcation.This method is most efficient and effective if the true input/output behavior of the simulation model can be approximated through a first-order polynomial possibly augmented with two-factor interactions.The method is explained and illustrated through three related discrete-event simulation models.These models represent three supply chain configurations, studied for an Ericsson factory in Sweden.After simulating 21 scenarios (factor combinations) each replicated five times to account for noise a shortlist with the 11 most important factors is identified for the biggest of the three simulation models.

KW - simulation

KW - bifurcation

KW - supply

KW - Sweden

M3 - Discussion paper

VL - 2003-104

T3 - CentER Discussion Paper

BT - Finding the Important Factors in Large Discrete-Event Simulation

PB - Operations research

CY - Tilburg

ER -

Kleijnen JPC, Bettonvil BWM, Persson F. Finding the Important Factors in Large Discrete-Event Simulation: Sequential Bifurcation and its Applications. Tilburg: Operations research. 2003. (CentER Discussion Paper).