Some interval-valued spherical fuzzy Frank Choquet integral operators in multicriteria decision making

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Pankaj Kakati, Bijan Davvaz
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Abstract

In real-life decision-making, expressing uncertainty, impreciseness, and hesitancy accurately is essential. Interval-valued spherical fuzzy sets (IVSFS) offer a suitable framework as an extension of interval-valued intuitionistic fuzzy sets, interval-valued picture fuzzy sets, and spherical fuzzy sets, allowing for interval-valued membership grades rather than exact values. This enhanced expressiveness enables more effective modeling of real-life decision-making problems by introducing suitable aggregation operators. In this paper, we propose the interval-valued spherical fuzzy Frank Choquet integral (IVSFFCI) and the interval-valued spherical fuzzy Frank geometric Choquet integral (IVSFFGCI) operators. These operators effectively capture the interaction among the criteria in real-life decision-making problems, overcoming the limitations of traditional methods. The IVSFFCI and IVSFFGCI operators utilize Frank’s t-norm and t-conorm, providing flexibility and robustness during the aggregation process. By considering the interrelation among the criteria, they exceed existing operators, making them the ideal choice for real-life decision-making situations. We develop a multicriteria decision-making (MCDM) method using the proposed operators that effectively deal with correlated criteria in real-life decision-making problems. To demonstrate the efficacy of the proposed method, an illustrative example relating to a financial body’s investment partner selection from four potential alternatives, based on criteria such as financial strength, mercantile expertise, entrepreneurial competencies, and risk management, is presented. The proposed method encapsulates immense potential across industries, promoting informed and data-driven decision-making processes.

Abstract Image

多标准决策中的一些区间值球形模糊弗兰克-乔凯积分算子
在现实决策中,准确表达不确定性、不精确性和犹豫不决性至关重要。区间值球形模糊集(IVSFS)作为区间值直观模糊集、区间值图像模糊集和球形模糊集的扩展,提供了一个合适的框架,允许使用区间值成员等级而不是精确值。通过引入合适的聚合算子,这种增强的表达能力可以更有效地模拟现实生活中的决策问题。在本文中,我们提出了区间值球形模糊弗兰克-乔凯积分(IVSFFCI)和区间值球形模糊弗兰克-几何乔凯积分(IVSFFGCI)算子。这些算子有效地捕捉了现实决策问题中标准之间的相互作用,克服了传统方法的局限性。IVSFFCI 和 IVSFFGCI 算子利用了 Frank 的 t-norm 和 t-conorm,在聚合过程中提供了灵活性和稳健性。通过考虑标准之间的相互关系,它们超越了现有的算子,成为现实决策情况下的理想选择。我们利用所提出的算子开发了一种多标准决策(MCDM)方法,可有效处理现实决策问题中的相关标准。为了证明所提方法的有效性,我们举了一个例子,说明金融机构如何根据财务实力、商业专长、创业能力和风险管理等标准,从四个潜在备选方案中选择投资合作伙伴。拟议的方法在各行各业都具有巨大的潜力,可促进知情和数据驱动的决策过程。
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来源期刊
Soft Computing
Soft Computing 工程技术-计算机:跨学科应用
CiteScore
8.10
自引率
9.80%
发文量
927
审稿时长
7.3 months
期刊介绍: Soft Computing is dedicated to system solutions based on soft computing techniques. It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. By linking the ideas and techniques of soft computing with other disciplines, the journal serves as a unifying platform that fosters comparisons, extensions, and new applications. As a result, the journal is an international forum for all scientists and engineers engaged in research and development in this fast growing field.
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