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使用灰狼优化器的基于售价相关需求的绿色产品不同类型的后期支付设施。

Different type of pay later facility for green product with selling price dependent demand using grey wolf optimizer.

作者信息

Alrasheedi Adel Fahad

机构信息

Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia.

出版信息

Heliyon. 2024 Jun 4;10(11):e32398. doi: 10.1016/j.heliyon.2024.e32398. eCollection 2024 Jun 15.

Abstract

The use of trade credit finance is becoming more widely acknowledged as a crucial approach to improving inventory system profitability. We review an inventory model with depending on permitted payment delays for which, if the retailer place an orders higher than or equal to a predefined quantity , then the supplier will provide a fully pay in later facility of periods (i.e., there will be no charge of interest until ). On the other hand the retailer need to pay a partial amount of payment to the supplier if the order quantity is less than , and the remaining amount may be deferred for up to periods. Main objective of this study is to investigate the inventory model with different situations under delayed payment facility. In addition, determining the product's demand also involves taking into account the item's greenness and selling price. We have also considered the fact that the cost of buying is influenced by the product's degree of greenness. We employ the meta heuristic algorithm Grey Wolf Optimizar (GWO) to assist us in solving the problem, and we compare the outcomes with the aid of a few other algorithms (Whale optimisation algorithm (WOA) and Artificial electric field algorithm (AEFA)). In the end, we resolve several numerical cases to support the model. The concavity of the desired function is graphically displayed using MATLAB software.

摘要

贸易信贷融资的使用作为提高库存系统盈利能力的关键方法正得到越来越广泛的认可。我们回顾一个依赖允许付款延迟的库存模型,对于该模型,如果零售商下达的订单高于或等于预定义数量 ,那么供应商将提供一个 期后的全额付款安排(即,直到 期都不会有利息费用)。另一方面,如果订单数量小于 ,零售商需要向供应商支付部分款项,剩余金额最多可延期 期。本研究的主要目的是研究在延迟付款安排下不同情形的库存模型。此外,确定产品需求还涉及考虑产品的绿色度和销售价格。我们还考虑了购买成本受产品绿色度影响这一事实。我们采用元启发式算法灰狼优化算法(GWO)来帮助我们解决问题,并借助其他一些算法(鲸鱼优化算法(WOA)和人工电场算法(AEFA))比较结果。最后,我们求解几个数值案例以支持该模型。使用MATLAB软件以图形方式显示目标函数的凹性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78a7/11219330/b446e3935b9b/gr1.jpg

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