Dynamic inventory replenishment strategy for aerospace manufacturing supply chain: combining reinforcement learning and multi-agent simulation

Author(s):  
Hao Wang ◽  
Jiaqi Tao ◽  
Tao Peng ◽  
Alexandra Brintrup ◽  
Edward Elson Kosasih ◽  
...  
Author(s):  
Souvik Barat ◽  
Prashant Kumar ◽  
Monika Gajrani ◽  
Harshad Khadilkar ◽  
Hardik Meisheri ◽  
...  

2016 ◽  
Vol 49 (12) ◽  
pp. 1245-1250 ◽  
Author(s):  
Nataliya N. Bakhtadze ◽  
Oleg V. Karsaev ◽  
Gulnara S. Smirnova ◽  
Rustem A. Sabitov ◽  
Boris M. Morozov ◽  
...  

2008 ◽  
pp. 2598-2617
Author(s):  
Jianxin Jiao ◽  
Xiao You ◽  
Arun Kumar

This chapter applies the multi-agent system paradigm to collaborative negotiation in a global manufacturing supply chain network. Multi-agent computational environments are suitable for dealing with a broad class of coordination and negotiation issues involving multiple autonomous or semi-autonomous problem-solving agents. An agent-based multi-contract negotiation system is proposed for global manufacturingsupply chain coordination. Also reported is a case study of mobile phone global manufacturing supply chain management.


Author(s):  
Jianxin Jiao ◽  
Xiao You ◽  
Arun Kumar

This chapter applies the multi-agent system paradigm to collaborative negotiation in a global manufacturing supply chain network. Multi-agent computational environments are suitable for dealing with a broad class of coordination and negotiation issues involving multiple autonomous or semi-autonomous problem-solving agents. An agent-based multi-contract negotiation system is proposed for global manufacturingsupply chain coordination. Also reported is a case study of mobile phone global manufacturing supply chain management.


2015 ◽  
Vol 36 ◽  
pp. 36-44 ◽  
Author(s):  
Sushma Kumari ◽  
Akshit Singh ◽  
Nishikant Mishra ◽  
Jose Arturo Garza-Reyes

2012 ◽  
Vol 6 (4) ◽  
pp. 215-226 ◽  
Author(s):  
G Jetly ◽  
C L Rossetti ◽  
R Handfield

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