Simulation-based optimisation of replenishment policy in supply chains

2021 ◽  
Vol 38 (2) ◽  
pp. 135
Author(s):  
Tomasz Wiśniewski ◽  
Rafał Szymański
2017 ◽  
Vol 43 ◽  
pp. 39-49 ◽  
Author(s):  
Hernán Chávez ◽  
Krystel K. Castillo-Villar ◽  
Luis Herrera ◽  
Agustín Bustos

2014 ◽  
Vol 2014 ◽  
pp. 1-21
Author(s):  
Hang Yang ◽  
Simon Fong ◽  
Yan Zhuang

Nowadays, a trend of forming dynamic supply chains with different trading partners over different e-marketplaces has emerged. These supply chains, which are called “supply mesh,” generally refer to heterogeneous electronic marketplaces in which dynamic supply chains, as per project (often make-to-order), are formed across different parties. Conceptually, in a supply mesh a dynamic supply chain is formed vertically, mediating several companies for a project. Companies that are on the same level horizontally are either competitors or cohorts. A complex scenario such as this makes it challenging to find the right group of members for a dynamic supply chain. Earlier on, a multiagent model called the collaborative single machine earliness/tardiness (CSET) model was proposed for the optimal formation of make-to-order supply chains. This paper contributes the particular agent designs, for enabling the mediation of CSET in a supply mesh, and the possibilities are discussed. It is demonstrated via a computer simulation, based on samples from the U.S. textile industry, that by using intelligent agents under the CSET model it is possible to automatically find an ideal group of trading partners from a supply mesh.


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