In an effort to compose an optimal supply chain (SC), this paper tries to bring forward a new collaborative agent-based single machine earliness/tardiness (SET) model. It includes the sub-agents, which are designed for fairly coordinating and distributing job requests at the mid-stream levels. Extending from the precedent SET model, collaborative-SET (CSET) has a coordinating collaborative agent, which is responsible for optimising the information flow and scheduling of the whole SC. This is done by coordinating the information flow at the sub-agent between each two streams. In a long run, this new model makes a complex dynamic SC more efficient and shortens response time. A stimulator that implements the algorithms is programmed in order to calculate the amount of information transfer, time and cost incurred between SET and CSET model. The results generally indicate that the more streams a SC has, the better the performance gain is yielded.
[1]
Ick-Hyun Nam.
Benefit of Supply Chain Coordination
,
2003
.
[2]
大野 耐一,et al.
Just-in-time for today and tomorrow
,
1988
.
[3]
Soongoo Hong,et al.
Optimal supply chain formation using agent negotiation in a SET model-based make-to-order
,
2006,
ICEC '06.
[4]
Menberu Lulu,et al.
Just-in-time (JIT) production and process unreliability
,
1986,
ANSS '86.
[5]
Richard F. Hartl,et al.
Pareto Ant Colony Optimization: A Metaheuristic Approach to Multiobjective Portfolio Selection
,
2004,
Ann. Oper. Res..
[6]
Simon Fong,et al.
Applying Pareto-Optimal and JIT Techniques for Supply Chains
,
2008,
2008 Eighth International Conference on Hybrid Intelligent Systems.