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ارائه مدل مدیریت موجودی توسط فروشنده در زنجیره تأمین دو سطحی محصولات فاسدشدنی تحت تقاضای تصادفی | ||
| مدیریت زنجیره تأمین | ||
| دوره 25، شماره 81، اسفند 1402، صفحه 1-15 اصل مقاله (1.4 M) | ||
| نوع مقاله: پژوهشی | ||
| نویسندگان | ||
| اعظم مدرس1؛ ناصر مطهری فریمانی* 2؛ فرزاد دهقانیان3 | ||
| 1دانشجوی دکترای مدیریت صنعتی، دانشگاه فردوسی مشهد، دانشکده علوم اداری و اقتصاد، مشهد، ایران | ||
| 2دانشیار گروه مدیریت، دانشگاه فردوسی مشهد، دانشکده علوم اداری و اقتصاد، مشهد، ایران | ||
| 3دانشیار گروه صنایع، دانشگاه فردوسی مشهد، دانشکده مهندسی، مشهد، ایران | ||
| تاریخ دریافت: 22 اسفند 1401، تاریخ بازنگری: 04 آذر 1402، تاریخ پذیرش: 18 بهمن 1402 | ||
| چکیده | ||
| یکی از رایجترین و موفقترین رویکردها برای مدیریت یکپارچه زنجیرهتأمین سیاست موجودی مدیریت شده توسط فروشنده است. در این سیاست، یک فروشنده کنترل تصمیمات موجودی را برای تعدادی از خردهفروشان در دست میگیرد. در این تحقیق سعی بر آن است تا برنامهریزی برای عرضه، تولید و توزیع با رویکردی یکپارچه برای کاهش ضایعات و کمبود محصولات فاسدشدنی به گونه‌ای مورد بررسی قرار گیرد که هزینه‌های فروشنده و خردهفروشان در زنجیرهتأمین با در نظر گرفتن سیاست موجودی مدیریت شده توسط فروشنده به کمترین حد خود برسد. از آنجایی که کاهش هزینه‌های ضایعات، کمبود، تولید و ذخیره‌سازی کالاهای فاسدشدنی از اهمیت بالایی برخوردار است، در این تحقیق به طور همزمان در مدل پیشنهادی بررسی می‌شوند. در این پژوهش، چون تقاضا وابسته به کیفیت محصول است و اطلاعات کیفیت برای خردهفروش قبل از تولید در دسترس نیست، تقاضا تصادفی و از توزیع مشخصی پیروی میکند. از آنجایی که برنامهریزی محدودیت شانسی بهعنوان ابزاری قوی برای سامانههای تصمیمگیری تصادفی معرفی شده است، در این مطالعه مسئله مورد نظر با استفاده از برنامهریزی محدودیت شانسی مدل شده است. در نهایت، کارایی روش ارائه شده از طریق مطالعه موردی زنجیرهتأمین مواد غذایی تایید شد. نتایج نشان داد که کاهش ضریب اطمینان در محدودیتهای شانسی میتواند بسیاری از هزینهها را در سازمان کاهش دهد. این تحقیق میتواند به مدیران زمانی که کاهش هزینه ضایعات و کمبود و تأمین تقاضا از اهمیت بالایی برخوردار است کمک شایانی بکند. | ||
| کلیدواژه‌ها | ||
| مدیریت موجودی توسط فروشنده؛ برنامهریزی محدودیت شانسی؛ زنجیرهتأمین؛ محصولات فاسدشدنی | ||
| عنوان مقاله [English] | ||
| Presentating a Model for the Vendor-Managed Inventory in a Two-Tier Supply Chain of Perishable Products Under Demand Uncertainty | ||
| نویسندگان [English] | ||
| Azam Modares1؛ Nasser Motahari Farimani2؛ Farzad Dehghanian3 | ||
| 1university of Ferdowsi | ||
| 2University of Ferdowsi,Faculty of managment | ||
| 3university of Ferdowsi | ||
| چکیده [English] | ||
| One of the most common and successful approaches to integrated supply chain management is vendor-managed Inventory. In this policy, a vendor takes control of inventory decisions for a number of retailers. This research aims to examine planning for supply, production, and distribution with an integrated approach to reduce waste and shortages of perishable products in a manner that minimizes costs for both the vendor and retailers in the supply chain, considering the vendor-managed Inventory. Since reducing the costs of waste, shortages, production, and storage of perishable goods is of paramount importance, this research simultaneously investigates the proposed model. In this study, as demand depends on product quality and quality information is not available to the retailer before production, demand follows a random and specific distribution. Since chance constraint programming has been introduced as a powerful tool for decision-making systems, in this study, the problem is modeled using this technique. Ultimately, the effectiveness of the proposed method was validated through a case study of a food supply chain. The results indicated that reducing confidence intervals in stochastic constraints could significantly reduce costs within the organization. This research can provide valuable assistance to managers when reducing waste, shortages, and demand fulfillment is of utmost importance. | ||
| کلیدواژه‌ها [English] | ||
| Vendor-Managed Inventory, Chance Constraint Programming, Supply Chain, Perishable Products | ||
| مراجع | ||
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آمار تعداد مشاهده مقاله: 322 تعداد دریافت فایل اصل مقاله: 394 |
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