Ranking fuzzy numbers by volume of solid of revolution of membership function about axis of support

IF 1.4 Q3 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
P. N. V. L. Sasikala, P. Phani Bushan Rao
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引用次数: 1

Abstract

It is admissible that fuzzy numbers (FNs) are apt for representing imprecise or vague data in real-world problems. While using FNs in decision-making problems, selecting the best alternative among available alternatives is challenging, and therefore, ranking FNs is essential. We can find different studies in the literature, but to our knowledge, no one attempted to rank FNs using the concept of volume. This paper proposes a new method for ranking generalized fuzzy numbers (GFNs) using the volume of the solid obtained by revolving its membership function (MF) about the x-axis. We calculate the volumes of positive and negative sides along with the centroid of a generalized fuzzy number(GFN) to define the fuzzy number(FN) score. This score represents the defuzzified value of FN, is used to select the best alternative, and overcomes the limitations in some existing methods like ranking FNs having the same centroid, crisp numbers, symmetric fuzzy numbers, and FNs with the same core.
根据支撑轴的隶属函数旋转体的体积对模糊数进行排序
在现实问题中,模糊数(FNs)适合表示不精确或模糊的数据,这是可以接受的。当在决策问题中使用FNs时,从可用的选项中选择最佳选项是具有挑战性的,因此,对FNs进行排序是必不可少的。我们可以在文献中找到不同的研究,但据我们所知,没有人试图使用体积的概念对FNs进行排名。本文提出了一种利用实体的体积对广义模糊数(gfn)进行排序的新方法,该方法由实体的隶属函数(MF)绕x轴旋转得到。我们计算了一个广义模糊数(GFN)的正负边的体积和质心来定义模糊数(FN)分数。该分数代表FN的去模糊化值,用于选择最佳备选方案,克服了现有方法对相同质心的FN、清晰数、对称模糊数、相同核心的FN进行排序的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Decision Science Letters
Decision Science Letters Decision Sciences-Decision Sciences (all)
CiteScore
3.40
自引率
5.30%
发文量
49
审稿时长
20 weeks
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