Sciweavers

Share
WSC
2007

Stability analysis of the supply chain by using neural networks and genetic algorithms

4 years 29 days ago
Stability analysis of the supply chain by using neural networks and genetic algorithms
Effectively managing a supply chain requires visibility to detect unexpected variations in the dynamics of the supply chain environment at an early stage. This paper proposes a methodology that captures the dynamics of the supply chain, predicts and analyzes future behavior modes, and indicates potentials for modifications in the supply chain parameters in order to avoid or mitigate possible oscillatory behaviors. Neural networks are used to capture the dynamics from the system dynamic models and analyze simulation results in order to predict changes before they take place. Optimization techniques based on genetic algorithms are applied to find the best setting of the supply chain parameters that minimize the oscillations. A case study in the electronics manufacturing industry is used to illustrate the methodology.
Alfonso Sarmiento, Luis Rabelo, Ramamoorthy Lakkoj
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2007
Where WSC
Authors Alfonso Sarmiento, Luis Rabelo, Ramamoorthy Lakkoju, Reinaldo J. Moraga
Comments (0)
books