人类学习下基于信用融资和缺货的模糊EOQ模型

M. Jayaswal, M. Mittal, Isha Sangal, Jayanti Tripathi
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引用次数: 2

摘要

本文建立了基于人类学习的贸易信用融资和欠单的库存模型。在该模型中,我们认为卖方向买方提供一个信用期来进行结算,买方接受有一定条款和条件的信用期政策。学习和信贷融资对地块规模和相应成本的影响已经提出。在模型的建立中,将需求和交货期作为模糊三角数进行模糊化,并对模糊数进行学习。首先放宽了对恒模糊性的考虑,然后将信贷融资下模糊学习的概念与表示相结合,假设模糊程度在规划范围内减小。最后,在信用融资和学习效应下,期望模糊总成本函数相对于订货量和发货量最小化。最后,通过数值算例给出了敏感分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy-Based EOQ Model With Credit Financing and Backorders Under Human Learning
In this paper, an inventory model has been developed with trade credit financing and back orders under human learning. In this model, it is considered that the seller provides a credit period to his buyer to settle the account and the buyer accepts the credit period policy with certain terms and conditions. The impact of learning and credit financing on the size of the lot and the corresponding cost has been presented. For the development of the model, demand and lead times have been taken as the fuzzy triangular numbers are fuzzified, and then learning has been done in the fuzzy numbers. First of all, the consideration of constant fuzziness is relaxed, and then the concept of learning in fuzzy under credit financing is joined with the representation, assuming that the degree of fuzziness reduces over the planning horizon. Finally, the expected total fuzzy cost function is minimized with respect to order quantity and number of shipments under credit financing and learning effect. Lastly, sensitive analysis has been presented as a consequence of some numerical examples.
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