基于区间犹豫模糊决策的应急救援中心选址研究

Research on Emergency Rescue Center Siting Based on Interval Valued Hesitant Fuzzy Decision-Making

摘要: 针对不同需求下基于犹豫模糊决策的应急救援中心选址问题，提出了一种基于区间犹豫模糊集(Interval Valued Hesitant Fuzzy Set, IVHFS)的新型混合选址方法。首先，根据决策者在面对多个评价指标、方案和变量时的犹豫性和模糊性做出的评价，构建区间值犹豫模糊集，即一个元素的隶属度用多个数值区间表示的集合，并利用最大偏差法确定各评价属性的权重值；然后，通过对传统的TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution)方法进行改进，提出了一种基于HF-TIPSIS (Hesistant Fuzzy Technique for Interval Preference by Similarity to an Ideal Solution)方法的应急救援中心选址模型；最后，结合犹豫模糊最大偏差法和HF-TIPSIS方法，将各备选地址与正负理想解的距离作为目标函数，充分考虑鲁棒偏差指标，采用绝对鲁棒和鲁棒偏差两种指标进行多目标鲁棒优化。通过算例验证了所提出的混合方法不仅能够保证专家评估信息的完整性和犹豫性，还能解决不确定条件下的模型参数扰动问题，从而为应急救援中心选址提供了一个有效的解决方案。

Abstract: In response to the emergency rescue center siting problem under various demands, a novel hybrid location selection method based on Interval Valued Hesitant Fuzzy Sets (IVHFS) is pro- posed. Firstly, the evaluative hesitancy and fuzziness faced by decision-makers when dealing with multiple evaluation criteria, scenarios, and variables are considered. This involves constructing Interval Valued Hesitant Fuzzy Sets, which represent membership degrees using multiple numerical intervals. The maximum deviation method is employed to determine the weights of each evaluation attribute. Subsequently, an improved approach to the traditional TOPSIS method is introduced, known as HF-TIPSIS, for emergency rescue center siting. Finally, integrating the Hesitant Fuzzy Maximum Deviation method and the HF-TIPSIS method, the objective function is defined by the distances between alternative sites and the positive and negative ideal solutions. Robust deviation metrics, including absolute robustness and robust deviation, are employed for multi-objective robust optimization. Case studies validate that the proposed hybrid method not only ensures the integrity and hesitancy of expert assessment information but also addresses model parameter perturbations under uncertain conditions, thereby providing an effective solution for emergency rescue center siting.