کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5081313 | 1477599 | 2011 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-objective ant colony optimisation: A meta-heuristic approach to supply chain design
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی صنعتی و تولید
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چکیده انگلیسی
This paper proposes a new approach to determining the Supply Chain (SC) design for a family of products comprising complex hierarchies of subassemblies and components. For a supply chain, there may be multiple suppliers that could supply the same components as well as optional manufacturing plants that could assemble the subassemblies and the products. Each of these options is differentiated by a lead-time and cost. Given all the possible options, the supply chain design problem is to select the options that minimise the total supply chain cost while keeping the total lead-times within required delivery due dates. This work proposes an algorithm based on Pareto Ant Colony Optimisation as an effective meta-heuristic method for solving multi-objective supply chain design problems. An experimental example and a number of variations of the example are used to test the algorithm and the results reported using a number of comparative metrics. Parameters affecting the performance of the algorithm are investigated.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Production Economics - Volume 131, Issue 1, May 2011, Pages 407-420
Journal: International Journal of Production Economics - Volume 131, Issue 1, May 2011, Pages 407-420
نویسندگان
Luis A. Moncayo-MartÃnez, David Z. Zhang,