利用基于cvar的鲁棒可能性规划方法对信用销售进行调整

IF 1.9 4区 数学 Q1 MATHEMATICS
A. Yousefi, M. Pishvaee, E. Teimoury
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引用次数: 3

摘要

本研究的目的是建立一个乳品全球供应链规划模型,其中运营和财务维度适当整合,以调整信用销售策略。为了评价乳制品供应链的财务绩效,使用了经济增值指数和一些财务比率。该模型与以利润最大化为目标函数的传统方法进行了比较。同时,本研究首次将信用销售金额作为决策变量。该模型采用了一种新的风险度量方法,即模糊CVaR,来应对汇率和退货数量质量的不确定性。利用真实的乳制品供应链数据,分析和评估了该模型的有效性和效率。从所开发的模糊数学模型得到的结果分析表明,与以前开发的模型相比,利润增加,半方差减少。并通过数值实验分析了信用销售策略的指标和影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adjusting the credit sales using CVaR-based robust possibilistic programming approach
The purpose of this study is to develop a dairy global supply chain planning model in which operational and financial dimensions are appropriately integrated in order to adjust the credit sale strategy. In order to evaluate the financial performance of the dairy supply chain, economic value-added index and some financial ratios are used. The proposed model is compared to traditional approaches, which usually use the profit maximization as an objective function. Also, the amount of credit sales is considered as a decision variable for the first time in this research. The developed model utilized a new risk measure, i.e., the fuzzy CVaR, to cope with the uncertainty of the exchange rate and the quality and quantity of returned products. The effectiveness and efficiency of the proposed model are analyzed and assessed using the data of a real dairy supply chain. The analysis of results obtained from the developed fuzzy mathematical model shows an increase in profit and a reduction in semi-variance compared to previously developed models. Also, some numerical experiments analyses index and the impact of credit sales strategy.
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来源期刊
CiteScore
3.50
自引率
16.70%
发文量
0
期刊介绍: The two-monthly Iranian Journal of Fuzzy Systems (IJFS) aims to provide an international forum for refereed original research works in the theory and applications of fuzzy sets and systems in the areas of foundations, pure mathematics, artificial intelligence, control, robotics, data analysis, data mining, decision making, finance and management, information systems, operations research, pattern recognition and image processing, soft computing and uncertainty modeling. Manuscripts submitted to the IJFS must be original unpublished work and should not be in consideration for publication elsewhere.
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