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Multiple criteria ranking and choice with all compatible minimal cover sets of decision rules

机译:多个标准排名和选择以及所有兼容的最小决策规则集

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We introduce a new multiple criteria ranking/choice method that applies Dominance-based Rough Set Approach (DRSA) and represents the Decision Maker's (DM's) preferences with decision rules. The DM provides a set of pairwise comparisons indicating whether an outranking (weak preference) relation should hold for some pairs of reference alternatives. This preference information is structured using the lower and upper approximations of outranking (S) and non-outranking (S-c) relations. Then, all minimal-cover (MC) sets of decision rules being compatible with this preference information are induced. Each of these sets is supported by some positive examples (pairs of reference alternatives from the lower approximation of a preference relation) and it does not cover any negative example (pair of alternatives from the upper approximation of an opposite preference relation). The recommendations obtained by all MC sets of rules are analyzed to describe pairwise outranking and non-outranking relations, using probabilistic indices (estimates of probabilities that one alternative outranks or does not outrank the other). Furthermore, given the preference relations obtained in result of application of each MC set of rules on a considered set of alternatives, we exploit them using some scoring procedures. From this, we derive the distribution of ranks attained by the alternatives. We also extend the basic approach in several ways. The practical usefulness of the method is demonstrated on a problem of ranking Polish cities according to their innovativeness. (C) 2015 Elsevier B.V. All rights reserved.
机译:我们引入了一种新的多准则排序/选择方法,该方法应用了基于优势的粗糙集方法(DRSA),并用决策规则表示了决策者(DM)的偏好。 DM提供了一组成对的比较,指示是否应该对某些参考替代对保持优等(弱偏好)关系。该优先级信息是使用排名(S)和非排名(S-c)关系的上下近似构造的。然后,诱导与该偏好信息兼容的所有最小覆盖(MC)决策规则集。这些集合中的每一个都有一些肯定的例子(从偏好关系的较低近似对中的参考选择对)支持,并且不包括任何负面的例子(从相反的偏好关系的较高近似对中的选择对)。分析所有MC规则集获得的建议,以概率指数(一个替代方案排名高于或未超过另一个方案的概率的估计值)描述成对排名和非排名关系。此外,考虑到在考虑的一组备选方案上应用每条MC规则集而获得的偏好关系,我们使用一些计分程序对其进行利用。由此,我们得出了替代方案所获得的等级分布。我们还以几种方式扩展了基本方法。该方法的实用性在根据波兰城市的创新性进行排名的问题上得到了证明。 (C)2015 Elsevier B.V.保留所有权利。

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