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Tools for establishing dominance with linear partial information and attribute hierarchy

机译:用于建立具有线性部分信息和属性层次结构的优势的工具

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The multiple attribute decision-making problem is dealt with when a decision-maker incompletely articulates their preferences about the attribute weight and alternative value. Furthermore, the attribute tree, which is structured hierarchically, is considered. Techniques for establishing dominance with linear partial information are proposed in a hierarchically structured attribute tree. The linear additive value function under certainty is used in the model. The incompletely specified information constructs a feasible region of linear constraints and therefore the pairwise dominance relationship between alternatives leads to intractable non-linear programming. Hence, solution techniques are proposed to handle this difficulty. Also, to handle the tree structure, the attribute tree is break down into subtrees. Due to the recursive structure of the solution technique, the optimization results from subtrees can be used in computing the interval on the topmost attribute. The intervals computed by the proposed solution techniques can be used to establish the pairwise dominance relation between alternatives. The pairwise dominance relation will be represented as strict dominance and weak dominance, which have already been defined in previous research. [References: 26]
机译:当决策者未完全阐明他们对属性权重和替代值的偏好时,就会解决多属性决策问题。此外,考虑了层次结构的属性树。在分层结构的属性树中提出了利用线性部分信息建立优势的技术。在模型中使用确定性下的线性附加值函数。不完全指定的信息构成了线性约束的可行区域,因此,替代方案之间的成对优势关系导致了棘手的非线性规划。因此,提出了解决该问题的解决方案技术。同样,为了处理树结构,将属性树分解为子树。由于求解技术的递归结构,子树的优化结果可用于计算最顶层属性的间隔。所提出的解决方案技术计算的间隔可用于建立替代方案之间的成对优势关系。成对的优势关系将表示为严格的优势和弱优势,这在先前的研究中已经定义。 [参考:26]

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