An Advanced Learned Type-3 Fuzzy Logic-Based Hybrid System to Optimize Inventory Cost for a New Business Policy

IF 0.8 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Proceedings of the National Academy of Sciences, India Section A: Physical Sciences Pub Date : 2023-09-29 DOI:10.1007/s40010-023-00849-5
Anirban Tarafdar, Pinki Majumder, Uttam Kumar Bera
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Abstract

In this paper, a type-3 fuzzy logic-based system has been created by accumulating the demand as the input variable to design the ideal inventory level that would minimize the overall inventory cost for the economic order quantity model. The new adaptation law based on the extended Kalman filter, and the unscented Kalman filter is carried out to tune the rule parameters and antecedent parameters of the suggested IT3-FLS. A real-life data set is collected to feed and test the IT3-FLS model. Some statistical measures like root-mean-square error, variance, correlation coefficient (R), and Theil’s coefficient are calculated to examine the prediction accuracy. The lowest RMSE observed is 0.02138, and the highest R is 0.99975 for IT3-FLS. Furthermore, the optimal total variable cost is calculated by collecting the estimated inventory. Additionally, to demonstrate the applicability of the suggested methodology, one real-life issue and its managerial resolution have been highlighted.

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基于先进学习型3型模糊逻辑的混合系统优化新商业策略的库存成本
本文建立了一个基于3型模糊逻辑的系统,通过累积需求作为输入变量来设计经济订单数量模型中使总库存成本最小的理想库存水平。基于扩展卡尔曼滤波和无气味卡尔曼滤波的自适应律,对所建议的IT3-FLS的规则参数和前置参数进行了调整。收集了一组真实的数据来支持和测试IT3-FLS模型。通过计算均方根误差、方差、相关系数(R)、泰尔系数等统计指标来检验预测的准确性。IT3-FLS的RMSE最低为0.02138,R最高为0.99975。然后,通过收集估计库存来计算最优总可变成本。此外,为了证明所建议方法的适用性,强调了一个现实生活中的问题及其管理解决办法。
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2.60
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0.00%
发文量
37
审稿时长
>12 weeks
期刊介绍: To promote research in all the branches of Science & Technology; and disseminate the knowledge and advancements in Science & Technology
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