کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
384163 660841 2012 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A multi-agent system using iterative bidding mechanism to enhance manufacturing agility
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A multi-agent system using iterative bidding mechanism to enhance manufacturing agility
چکیده انگلیسی

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.


► An agent system to dynamically integrate process planning and production scheduling.
► Enhance manufacturing agility to cope with changes in the market and production.
► A currency-based iterative agent bidding mechanism to achieve operation optimisation.
► Currency values are tuned iteratively to obtain better and better production plans.
► A genetic algorithm is proposed to tune the currency values at each iteration.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 39, Issue 9, July 2012, Pages 8259–8273
نویسندگان
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