دانلود مقاله ISI انگلیسی شماره 50546
ترجمه فارسی عنوان مقاله

تجزیه و تحلیل بهینه سازی برنامه ریزی زنجیره تامین در مشتری گرایی انبوه

عنوان انگلیسی
Optimization analysis of supply chain scheduling in mass customization
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
50546 2009 15 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : International Journal of Production Economics, Volume 117, Issue 1, January 2009, Pages 197–211

ترجمه کلمات کلیدی
مشتری گرایی انبوه - برنامه ریزی زنجیره تامین - تناقضات غالب - بهینه سازی
کلمات کلیدی انگلیسی
Mass customization; Supply chain scheduling; Dominant contradictions; Optimization
پیش نمایش مقاله
پیش نمایش مقاله  تجزیه و تحلیل بهینه سازی برنامه ریزی زنجیره تامین در مشتری گرایی انبوه

چکیده انگلیسی

How to deal with the contradiction between scale production effect and customized demand is the key problem on studying mass customization (MC). When MC is operating in supply chain environment, on one hand, the excellent operating character of the supply chain will give conditions for solving this problem. On the other hand, it will bring out several complicated contradictions and increase the difficulties of the analysis and research on the supply chain operating and scheduling, so it is important to settle the contradictions. Based on our earlier work, the dominant contradictions of the supply chain scheduling in MC and the ways to relieve them are briefly summarized in this paper. A dynamic and multi-objective optimization mathematical model and the appropriate solving algorithm are set up by introducing these relieving methods into the operating process. It is pointed out that the characteristics of the model and algorithm cannot only reflect the unique operating requirements for this special production mode, but also merge with the thought of relieving the dominant contradictions. The feasibility of the model and algorithm in practical application to improve the scheduling efficiency and to settle the key problem mentioned above ultimately gets validated through the analysis of an application case we followed and through the algorithm simulation of a numerical scheduling case.