An algorithmic multiple attribute decision-making context to model uncertainty associated with hospital site selection problem using complex sv-neutrosophic soft information

Decision-making approaches are often used in uncertain environments by people who must make difficult judgments in daily life, including elements of varied qualities and costs. These methods assist decision-makers in managing ambiguity and uncertainty, allowing for more informed and risk-reduced decisions. This research introduces an advanced framework called a complex single-valued neutrosophic soft set (csvNSS) to address uncertainties inherent in decision-making. The csvNSS framework is capable of managing information periodicity by introducing two components: amplitude and phase. The first deals with fuzzy membership, while the second manages periodicity within a complex plane. Some rudiments of csvNSS like properties, set operations and aggregations, are investigated. To make these ideas practically applicable in choosing an appropriate location for the hospital, an algorithm for handling csvNSS is proposed. An enhanced strategy is validated through the use of a specific example that takes site selection for hospital into account. The outcome demonstrates the efficacy of the suggested strategy. The method can be used in other domains where selection issues arise.

决策方法常被应用于不确定环境中，供日常生活中需作出艰难抉择的主体使用，此类场景往往涵盖质量与成本各不相同的各类要素。此类方法可辅助决策者应对模糊性与不确定性，助力做出更具依据且风险更低的决策。本研究提出一种名为复单值中智软集（complex single-valued neutrosophic soft set，csvNSS）的先进框架，以解决决策过程中固有的不确定性问题。该复单值中智软集框架通过引入幅值与相位两个分量，实现对信息周期性的管理：其中前者用于处理模糊隶属度，后者则负责管控复平面内的周期性特征。本研究对复单值中智软集的若干基础内容展开了探究，包括其基本性质、集合运算与聚合算子等。为使该框架的相关理论可实际应用于医院选址问题，本研究提出了一种针对复单值中智软集的处理算法。通过一个针对医院选址的具体案例，对所提出的改进策略进行了有效性验证。实验结果证明了所提策略的有效性。该方法还可推广至其他存在选择类问题的领域。