دانلود مقاله ISI انگلیسی شماره 19196
عنوان فارسی مقاله

الگوریتم ژنتیک تنظیم شده با پارامتر برای مدل مقدار تولید اقتصادی چند محصولی با محدودیت فضا، سفارشات تحویلی گسسته و کمبود

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
19196 2010 9 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
A parameter-tuned genetic algorithm for multi-product economic production quantity model with space constraint, discrete delivery orders and shortages
منبع

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

Journal : Advances in Engineering Software, Volume 41, Issue 2, February 2010, Pages 306–314

کلمات کلیدی
الگوریتم ژنتیک - مدیریت موجودی - مقدار تولید اقتصادی - تحویل گسسته - کمبود - برگشت سفارش - طراحی آزمایشات -
پیش نمایش مقاله
پیش نمایش مقاله الگوریتم ژنتیک تنظیم شده با پارامتر برای مدل مقدار تولید اقتصادی چند محصولی با محدودیت فضا، سفارشات تحویلی گسسته و کمبود

چکیده انگلیسی

In this paper, a multi-product economic production quantity problem with limited warehouse-space is considered in which the orders are delivered discretely in the form of multiple pallets and the shortages are completely backlogged. We show that the model of the problem is a constrained non-linear integer program and propose a genetic algorithm to solve it. Moreover, design of experiments is employed to calibrate the parameters of the algorithm for different problem sizes. At the end, a numerical example is presented to demonstrate the application of the proposed methodology.

مقدمه انگلیسی

The economic production quantity (EPQ) is one of the most applicable models in production and inventory control environments. This model can be considered as an extension to the well-known economic order quantity (EOQ) model that was introduced by Harris [1] in 1913. Regardless of the simplicity of EOQ and EPQ, they are still applied industry-wide today [2]. In spite of wide acceptance, some practitioners and researchers have questioned the practical applications of the EOQ model due to several unrealistic assumptions regarding model input parameters. These parameters are setup costs, holding costs and demand rate. For example Woolsey [3] severely critiqued the use of the EOQ model, arguing that the assumptions (i.e. constant demand, fixed carrying capacity, constant price, unlimited storage capacity, and paying for the price of items as soon as they are received) necessary to justify the use of this model are not met in real world environment. This has motivated many researchers to modify the EOQ model to match real-life situations. Chang et al. [4] developed an EOQ model for deteriorating items, in which the supplier provides a permissible delay to the purchaser if the order quantity is greater than or equal to a predetermined quantity. Li et al. [5] developed EPQ-based models with planned backorders to evaluate the impact of the postponement strategy on a manufacturer in a supply chain. They derived the optimal total average costs per unit time for producing and keeping end-products in a postponement system and a non-postponement system, respectively.

نتیجه گیری انگلیسی

In this paper a multi-product EPQ model with limited warehouse space was presented in which the orders were delivered discretely in the form of multiple pallets. Moreover, it was assumed that the shortages were allowed and were completely backlogged. Under these conditions, the problem was formulated as a non-linear integer-programming model and a parameter-tuned genetic algorithm was proposed to solve it.

خرید مقاله
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