Fuzzy Preference Ordering of Interval Numbers in Decision Problems
Fuzzy Preference Ordering of Interval Numbers in Decision Problems
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DOI：
10.1007/978-3-540-89915-0
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发表时间：
2009-02
期刊：
影响因子：
--
通讯作者：
Atanu Sengupta;T. Pal
中科院分区：
文献类型：
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作者：
Atanu Sengupta;T. Pal
在传统的数学规划中，在经典的数学推理中，问题的系数通常由专家确定为明确的值。但在现实中，在不精确和不确定的环境中，假设专家的知识和表达可以以精确的方式出现是非常不现实的。本书更广泛的目标是研究不同的真实决策情况，其中问题是在不精确的环境中定义的。不精确性主要通过两种方式产生--(1)由于人类专家的不精确感知和知识，然后将知识模糊地表示为数据挖掘；(2)由于问题情境定义中的关系和数据结构的海量和复杂性。我们使用区间数来指定不准确、不精确或不确定的数据。因此，研究决策问题需要回答以下初始问题--
In conventional mathematical programming, coefficients of problems are usually determined by the experts as crisp values in terms of classical mathematical reasoning. But in reality, in an imprecise and uncertain environment, it will be utmost unrealistic to assume that the knowledge and representation of an expert can come in a precise way.The wider objective of the book is to study different real decision situations where problems are defined in inexact environment. Inexactness are mainly generated in two ways–(1) due to imprecise perception and knowledge of the human expert followed by vague representation of knowledge as a DM;(2) due to hugeness and complexity of relations and data structure in the definition of the problem situation. We use interval numbers to specify inexact or imprecise or uncertain data. Consequently, the study of a decision problem requires answering the following initial questions–