A Bayesian Approach to Portfolio Selection in Multicriteria Group Decision Making
A Bayesian Approach to Portfolio Selection in Multicriteria Group Decision Making
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DOI：
10.1016/j.procs.2015.08.618
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
M. Emmerich;A. Deutz;I. Yevseyeva
中科院分区：
文献类型：
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作者：
M. Emmerich;A. Deutz;I. Yevseyeva
在多标准决策的后验方法中，其思想是首先找到一组有趣的（通常是非支配的）决策备选方案，然后让决策者从中选择。通常，一个额外的要求是将备选方案的大小限制为少量解决方案。在这种情况下，说明集合上的偏好是很重要的。在以前的工作中，已经表明目标函数的独立归一化（例如使用可取性函数）与hypervolume指示器相结合可以用来制定这样的集偏好。建立了计算一组解包含至少一个满意解的概率并使其最大化的程序。此外，我们将模型扩展到多个决策者的场景。为此，我们计算给定集合中至少有一个解满足所有决策者的概率。首先，考虑从决策者那里先验地获得的信息。然后，介绍了计算单个集合中存在所有决策者都能接受的解的概率的计算过程。然后，我们讨论了如何减少计算量以及如何使度量最大化。将讨论在数据库查询中使用这种方法的实际示例，以便展示这种方法如何与应用程序相关联。
In the a-posteriori approach to multicriteria decision making the idea is to first find a set of interesting (usually non-dominated) decision alternatives and then let the decision maker select among these.Often an additional demand is to limit the size of alternatives to a small number of solutions. In this case, it is important to state preferences on sets. In previous work it has been shown that independent normalization of objective functions (using for instance desirability functions) combined with the hypervolume indicator can be used to formulate such set-preferences.A procedure to compute and to maximize the probability that a set of solutions contains at least one satisfactory solution is established. Moreover, we extend the model to the scenario of multiple decision makers. For this we compute the probability that at least one solution in a given set satisfies all decision makers. First, the information required a-priori from the decision makers is considered. Then, a computational procedure to compute the probability for a single set to contain a solution, which is acceptable to all decision makers, is introduced. Thereafter, we discuss how the computational effort can be reduced and how the measure can be maximized. Practical examples for using this in database queries will be discussed, in order to show how this approach relates to applications.