دانلود مقاله ISI انگلیسی شماره 83457
ترجمه فارسی عنوان مقاله

طراحی شبکه زنجیره تامین انعطاف پذیر در زیر عدم اطمینان

عنوان انگلیسی
Flexible supply chain network design under uncertainty
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
83457 2017 36 صفحه PDF
منبع

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

Journal : Chemical Engineering Research and Design, Volume 128, December 2017, Pages 290-305

ترجمه کلمات کلیدی
طراحی شبکه زنجیره تامین، عدم قطعیت تقاضا، رویکرد سناریو، برنامه ریزی تصادفی، زنجیره تامین انعطاف پذیر،
کلمات کلیدی انگلیسی
Supply chain network design; Demand uncertainty; Scenario approach; Stochastic programming; Flexible supply chains;
پیش نمایش مقاله
پیش نمایش مقاله  طراحی شبکه زنجیره تامین انعطاف پذیر در زیر عدم اطمینان

چکیده انگلیسی

Flexibility in supply chain networks dealing with uncertainty, has become a research challenge over the past years. This work proposes a flexible supply chain network design (SCND) model that uses generalized production/warehousing nodes instead of individual production plants and warehouses while conquers with demand uncertainty using a scenario-based approach. It also deals with inventory management and decisions on strategical and tactical level (facility location, production rate, warehouse capacity, demand allocation between generalized nodes, inventory levels, product flows, suppliers’ product availability and links between all facilities). The proposed Mixed-Integer Linear Programming (MILP) model allows intra-layer flows between generalized nodes and aims at minimizing total network cost. A case study is formed to test the applicability of the model for a medium sized European company. A comparison was made between a classic supply chain network and generalized network that deals with uncertainty. Results have revealed cost benefits for this model, making it not only applicable, but also cost effective for the company that will apply it. This decision support system, can help managers in taking strategic decisions such as facility location, with a higher level of accuracy.