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A new efficient collaboration model for multi-echelon supply chains
- Source :
- Expert Systems with Applications. 128:54-66
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Extensive research has shown that collaboration has substantial impact on supply chains performance. However, most of previous research has focused on information sharing-based collaboration models that require considerable effort to be implemented, such as information exchange supply chain (IESC). This paper introduces a new efficient collaboration model (IS-OUT) for multi-echelon supply chains. The IS-OUT model relies upon the ordering mechanism of the classical order-up-to policy (OUT). In traditional supply chains (TSC), although OUT replenishment orders include two pieces of information: demand forecast and inventory position balance, they are transferred to upstream echelons as single-quantity orders. In IS-OUT, the order information is transferred to the upstream echelons as two component parts of information to provide better coordination in supply chains. In this paper, the mathematical formulation of IS-OUT is presented, and simulation is adopted to compare the performance of TSC, IS-OUT, and IESC under special conditions and assumptions, considering various performance metrics. Although the results indicate that IESC model offers higher performance mostly than IS-OUT, IS-OUT outperforms or at least is comparable with IESC under a few conditions. Since IS-OUT model is easier to implement than IESC, IS-OUT provides a compromise between extent and information sharing requirements, and performance efficiency. The results should help a decision maker to select the model that optimizes its operating environment.
- Subjects :
- 0209 industrial biotechnology
fill rate
Operations research
Computer science
Supply chain
02 engineering and technology
020901 industrial engineering & automation
Artificial Intelligence
Order (exchange)
Component (UML)
0202 electrical engineering, electronic engineering, information engineering
Bullwhip
Information exchange
Upstream (petroleum industry)
Cobullwhip
Classical order-up-to
classical order-up-to
collaboration
information sharing
multi-echelon supply chain
net stock amplification
simulation
stress demand
Information sharing
General Engineering
Demand forecasting
Computer Science Applications
020201 artificial intelligence & image processing
Hardware_LOGICDESIGN
Subjects
Details
- ISSN :
- 09574174
- Volume :
- 128
- Database :
- OpenAIRE
- Journal :
- Expert Systems with Applications
- Accession number :
- edsair.doi.dedup.....0472336b4f55e6d6bdf04974d3c408c3