Purpose

Decision-making is always an issue that managers have to deal with. Keenly observing to different preferences of the targets provides useful information for decision-makers who do not require too much information to make decisions. The main purpose is to avoid decision-makers in a dilemma because of too much or opaque information. Based on problem-oriented, this research aims to help decision-makers to develop a macro-vision strategy that fits the needs of different clusters of customers in terms of their favorite restaurants. This research also focuses on providing the rules to rank data sets for decision-makers to make choices for their favorite restaurant.

Design/methodology/approach

When the decision-makers need to rethink a new strategic planning, they have to think about whether they want to retain or rebuild their relationship with the old consumers or continue to care for new customers. Furthermore, many of the lecturers show that the relative concept will be more effective than the absolute one. Therefore, based on rough set theory, this research proposes an algorithm of related concepts and sends questionnaires to verify the efficiency of the algorithm.

Findings

By feeding the relative order of calculating the ranking rules, we find that it will be more efficient to deal with the faced problems.

Originality/value

The algorithm proposed in this research is applied to the ranking data of food. This research proves that the algorithm is practical and has the potential to reveal important patterns in the data set.

中文翻译：

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数据排名的相对决策算法

目的

决策始终是经理必须处理的问题。敏锐地观察目标的不同偏好，为不需要太多信息来进行决策的决策者提供有用的信息。主要目的是避免决策者因信息过多或不透明而陷入困境。基于问题导向的研究，该研究旨在帮助决策者制定宏观战略，以根据其最喜欢的餐厅满足不同客户群的需求。这项研究还着重于提供规则以对数据集进行排名，以使决策者可以选择自己喜欢的餐厅。

设计/方法/方法

当决策者需要重新考虑新的战略计划时，他们必须考虑是要保留还是重建与老客户的关系，还是继续照顾新客户。此外，许多讲师表明相对概念将比绝对概念更有效。因此，本研究基于粗糙集理论，提出了一种相关概念的算法，并通过发送问卷的方式验证了算法的有效性。

发现

通过提供计算排名规则的相对顺序，我们发现处理面临的问题将更加有效。

创意/价值

该研究提出的算法被应用于食品的排名数据。这项研究证明该算法是实用的，并且有可能揭示数据集中的重要模式。