Name
Title | ||
|---|---|---|
Simulation and optimization of supply chains: alternative or complementary approaches? |
Abstract | ||
|---|---|---|
Discrete-event simulation and (mixed-integer) linear programming are widely used for supply chain planning. We present a general
framework to support the operational decisions for supply chain networks using a combination of an optimization model and
discrete-event simulation. The simulation model includes nonlinear and stochastic elements, whereas the optimization model
represents a simplified version. Based on initial simulation runs cost parameters, production, and transportation times are
estimated for the optimization model. The solution of the optimization model is translated into decision rules for the discrete-event
simulation. This procedure is applied iteratively until the difference between subsequent solutions is small enough. This
method is applied successfully to several test examples and is shown to deliver competitive results much faster compared to
conventional mixed-integer models in a stochastic environment. It provides the possibility to model and solve more realistic
problems (incorporating dynamism and uncertainty) in an acceptable way. The limitations of this approach are given as well. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s00291-007-0118-z | Or Spektrum |
Keywords | Field | DocType |
hybrid method,discrete-event simulation,supply chain management,optimization,decision rule,discrete event simulation,supply chain,simulation model | Decision rule,Dynamism,Mathematical optimization,Economics,Nonlinear system,Supply chain planning,Supply chain management,Linear programming,Supply chain,Operations management,Discrete event simulation | Journal |
Volume | Issue | ISSN |
31 | 1 | 0171-6468 |
Citations | PageRank | References |
22 | 1.00 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Almeder | 1 | 90 | 7.09 |
| Margaretha Preusser | 2 | 22 | 1.34 |
| Richard F. Hartl | 3 | 1863 | 137.30 |