Title
Using Particle Swarm Optimization With A Policy Optimization Approach To Stabilize The Supply Chain
Abstract
In this paper, we propose and demonstrate a new methodology to stabilize systems with complex dynamics like the supply chain. This method is based on the Accumulated Deviations from Equilibrium (ADE). It is most beneficial for controlling system dynamic models characterized by multiple types of delays, many interacting variables, and feedback processes. We employ Particle Swarm Optimization as the optimization approach due to its performance in multi-dimensional space, stochastic properties, and global reach. We demonstrate the effectiveness of our method using a manufacturing-supply-chain case study. ©2009 IEEE.
Publication Date
12-1-2009
Publication Title
Proceedings - Winter Simulation Conference
Number of Pages
851-862
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/WSC.2009.5429712
Copyright Status
Unknown
Socpus ID
77951613101 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/77951613101
STARS Citation
Sarmiento, Alfonso T.; Rabelo, Luis; and Jones, Albert, "Using Particle Swarm Optimization With A Policy Optimization Approach To Stabilize The Supply Chain" (2009). Scopus Export 2000s. 11405.
https://stars.library.ucf.edu/scopus2000/11405