دانلود مقاله ISI انگلیسی شماره 42900
ترجمه فارسی عنوان مقاله

مدل موجودی تولید برای اقلام فاسدشدنی با تقاضای نوع رمپ با حضور تورم و کمبود تحت فازی بودن

عنوان انگلیسی
A production inventory model for deteriorating item with ramp type demand allowing inflation and shortages under fuzziness
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
42900 2015 12 صفحه PDF
منبع

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

Journal : Economic Modelling, Volume 46, April 2015, Pages 334–345

ترجمه کلمات کلیدی
نرخ تقاضا نوع شیب دار - تخریب - تورم - کمبود - عدد فازی مثلثی - فهرست
کلمات کلیدی انگلیسی
Ramp-type demand rate; Deterioration; Inflation; Shortage; Triangular fuzzy number; Inventory
پیش نمایش مقاله
پیش نمایش مقاله  مدل موجودی تولید برای اقلام فاسدشدنی با تقاضای نوع رمپ با حضور تورم و کمبود تحت فازی بودن

چکیده انگلیسی

Economic production quantity (EPQ) is the quantity of a product that should be manufactured in a single batch so as to minimize the total cost. In classical model EPQ only applies where the demand for a product and production rate is constant over the year. But in reality these parameters vary with time in different scenarios. In this paper we have considered a production inventory model for deteriorating items with ramp type demand rate under the effect of inflation and shortages under fuzziness. The deterioration rate is represented by a two-parameter Weibull distribution. As inflation erodes the value of money so we have also considered the effect of inflation when there is shortage in the stock under finite time horizon. Some parameters are vaguely or unclearly defined or whose values are imprecise or determined based on subjective beliefs of individuals. Therefore the inventory model is solved under fuzzy environment to evaluate the optimum solution of the model in different cases. We have optimized our solution by considering production time and production rate as decision variables in two separate cases. While incorporating symmetric triangular fuzzy number we use total λ-integral value to defuzzify the solution. Finally, utility of the model is presented by using some numerical examples and sensitivity analysis and the results are analyzed.