A multi-agent system using iterative bidding mechanism to enhance manufacturing agility

M.K. Lim, Z. Zhang
Expert Systems with Applications, Volume 39, Issue 9, July 2012

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.

Summary: This paper introduced a currency-based iterative agent bidding mechanism used as an agent coordination mechanism in a multi-agent system (MAS). It is aimed at integrating the activities associated with production planning and control in order to enhance the agility, responsiveness and flexibility of manufacturing systems in coping with dynamic changes in the market and to achieve near-optimum solutions to integrated process plan and schedule problems. The mechanism enables process planning options and production scheduling options to be evaluated dynamically and optimised simultaneously, so as to generate optimised process plans and schedules. The MAS also provides a platform where the possible reconfiguration of manufacturing systems can be assessed and the utilisation of manufacturing resources can be optimised. To facilitate the iterative bidding mechanism, GA optimisation technique was employed to adjust the current values. A test case was used to simulate the agent bidding mechanism and various test runs (by means of changing the values of GA parameters, as well as under dynamic environment such as machines failure and urgent pre-emptive jobs) were executed to evaluate the effectiveness of the proposed GA technique. The simulation results show that as the currency values were adjusted iteratively, the production cost of producing the components was gradually reduced. The results were then compared to the results obtained based on three non-agent integrated process planning and production scheduling systems (Khoshnevis & Chen 1993, Usher & Fernandes 1996b, and Saygin & Kilic 1999). The comparative results show that the MAS performs better than the non-agent systems. The MAS evaluates and optimises process plans and production schedules simultaneously. It allows agents that representing the machines to bid for jobs based on their capability and best performance (e.g. to maximise their machine utilisation). With this approach, a near-optimum solution can be achieved and the utilisation of manufacturing resources can also be optimised.

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