求解中性微分方程的存在性和唯一性条件及其对最优订货量策略的影响

Logistics Pub Date : 2024-02-08 DOI:10.3390/logistics8010018
A. F. Momena, Rakibul Haque, M. Rahaman, S. Salahshour, S. Mondal
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引用次数: 0

摘要

背景:中性逻辑明确量化了不确定性,同时还保持了真性、不确定性和假性成员函数的独立性。在必须处理相互矛盾或不充分数据的情况下,这一特性显得尤为重要。在不确定性背景下探索微分方程已成为一个不断发展的研究领域。方法:本研究提出了一阶线性中性微分方程的可解条件。本研究还证明了中性微分方程解的存在性和唯一性,随后使用广义中性导数简明地表达了该解。作为一阶中性微分方程的应用,我们讨论了中性环境下的经济批量模型。研究结果本研究发现了一阶中性微分方程现有解的条件。通过数值模拟,本研究还发现中性微分方程方法更适合处理库存控制问题中涉及的不确定性。结论:本文介绍了微分方程原理及其在中性环境中的应用。这种方法可用于任何运营研究或决策场景,以消除不确定性并获得更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Existence and Uniqueness Conditions for Solving Neutrosophic Differential Equations and Its Consequence on Optimal Order Quantity Strategy
Background: Neutrosophic logic explicitly quantifies indeterminacy while also maintaining the independence of truth, indeterminacy, and falsity membership functions. This characteristic assumes an imperative part in circumstances, where dealing with contradictory or insufficient data is a necessity. The exploration of differential equations within the context of uncertainty has emerged as an evolving area of research. Methods: the solvability conditions for the first-order linear neutrosophic differential equation are proposed in this study. This study also demonstrates both the existence and uniqueness of a solution to the neutrosophic differential equation, followed by a concise expression of the solution using generalized neutrosophic derivative. As an application of the first-order neutrosophic differential equation, we discussed an economic lot sizing model in a neutrosophic environment. Results: This study finds the conditions for the existing solution of a first-order neutrosophic differential equation. Through the numerical simulation, this study also finds that the neutrosophic differential equation approach is much better for handling uncertainty involved in inventory control problems. Conclusions: This article serves as an introductory exploration of differential equation principles and their application within a neutrosophic environment. This approach can be used in any operation research or decision-making scenarios to remove uncertainty and attain better outcomes.
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