Brintrup, Alexandra (2010) Multi-agent, multi-role, and multi-objective supply chain behaviour optimisation. Computers in Industry, 61 (7). pp. 636-645.
Researchers, practitioners and enterprise software providers are realising the potential of agent-based technology to automate supply chain procurement to achieve consistent, traceable decision making. As the complexity of supply chains grow, these systems will gain more attention. In this paper, we model and simulate a complex autonomous supply chain managed by computational agents that aim to minimise lead time and maximise revenue through evolutionary multi-objective optimisation. The agents are in a competitive environment where they take on the roles of both client and producer. In addition to optimising their production strategy, they also have the opportunity to dynamically fine-tune their decision parameters when it comes to selecting their own suppliers, using the Analytical Hierarchy Process. It is observed that computational agents are capable of functioning in such complex environments, effectively converging to policies in synergy with their market. Multi-objective, multi-role optimisation results in better overall supply chain performance than tests where agents have single-objectives and single-roles. Our study forms an exploratory step towards more realistic agent-based supply chains where analytical methods are unavailable.
|Keywords:||multi agent systems; Multi-objective supply chain optimisation; Multi-criteria decision making|
|Centre:||CABDyN Complexity Centre|
|Date Deposited:||26 Oct 2011 14:19|
|Last Modified:||23 Oct 2015 14:05|
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