کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9663778 | 1446242 | 2005 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Knowledge-based framework for automated dynamic supply chain configuration
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Supply chain management has gained renewed interest among researchers in recent years. This is primarily due to the availability of timely information across the various stages of the supply chain, and therefore the need to effectively utilize the information for improved performance. Although information plays a major role in effective functioning of supply chains, there is a paucity of studies that deal specifically with the dynamics of supply chains and how data collected in these systems can be used to improve their performance. In this paper I develop a framework, with machine learning, for automated supply chain configuration. Supply chain configuration used to be mostly a one-shot problem. Once a supply chain is configured, researchers and practitioners were more interested in means to improve performance given that initial configuration. However, recent developments in e-commerce applications and faster communication over the Internet in general necessitates dynamic (re)configuration of supply chains over time to take advantage of better configurations. Using examples, I show performance improvements of the proposed adaptive supply chain configuration framework over static configurations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 165, Issue 1, 16 August 2005, Pages 219-230
Journal: European Journal of Operational Research - Volume 165, Issue 1, 16 August 2005, Pages 219-230
نویسندگان
Selwyn Piramuthu,