Lim, M.K. and Zhang, Z. (2012) A multi-agent system using iterative bidding mechanism to enhance manufacturing agility. Expert Systems with Applications, 39(9), pp. 8259-8273. (doi: 10.1016/j.eswa.2012.01.160)
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Abstract
The global market has become increasingly dynamic, unpredictable and customer-driven. This has led to rising rates of new product introduction and turbulent demand patterns across product mixes. As a result, manufacturing enterprises were facing mounting challenges to be agile and responsive to cope with market changes, so as to achieve the competitiveness of producing and delivering products to the market timely and cost-effectively. This paper introduces a currency-based iterative agent bidding mechanism to effectively and cost-efficiently integrate the activities associated with production planning and control, so as to achieve an optimised process plan and schedule. The aim is to enhance the agility of manufacturing systems to accommodate dynamic changes in the market and production. The iterative bidding mechanism is executed based on currency-like metrics; each operation to be performed is assigned with a virtual currency value and agents bid for the operation if they make a virtual profit based on this value. These currency values are optimised iteratively and so does the bidding process based on new sets of values. This is aimed at obtaining better and better production plans, leading to near-optimality. A genetic algorithm is proposed to optimise the currency values at each iteration. In this paper, the implementation of the mechanism and the test case simulation results are also discussed.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Lim, Professor Ming |
| Authors: | Lim, M.K., and Zhang, Z. |
| College/School: | College of Social Sciences > Adam Smith Business School > Management |
| Journal Name: | Expert Systems with Applications |
| Publisher: | Elsevier |
| ISSN: | 0957-4174 |
| Published Online: | 02 February 2012 |
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