Purpose: This study proposes a new two-stage clustering method to break down the symmetric multiple traveling salesman …-programming model. A comparison with the k-means++ clustering algorithm, one of the most popular clustering algorithms, was made to … study tackles the issue of improving the performance of clustering-based optimization approaches in solving the mTSP by …

heterogeneous insurance data. Additionally, we adapt spectral clustering, a technique based on graph theory that accommodates non …The K-means algorithm and its variants are well-known clustering techniques. In actuarial applications, these …-established clustering methods to complex insurance datasets containing both categorical and numerical variables. To achieve this, we propose …

The goal of the paper is to present the framework for combining clustering and classification for churn management in … approach to churn management using clustering and classification, which was tested on the churn dataset with a rich variable …

Purpose: Automatic grouping of data according to certain characteristics is made possible by clustering algorithms … without shortcomings, suggesting that there is ample room for improvement. This paper briefly introduces clustering techniques … of clustering techniques. Originality/value: To date, there has been no paper comparing the new k-value estimation …

, distortions, and poor decisions. The presence of missing values in data introduces inaccuracies in clustering and classification … comparing the performance of imputation techniques using clustering metrics and algorithms (e.g., k-means, Partitioning Around …

geographical distribution of smuggling within a country. In this regard, clustering techniques (both classical and spatial analysis …

authority aims to find the best location-allocation solution by clustering clients and assigning facilities to these clusters …

Development Index (HDI) through Multiple Factor Analysis (MFA) and hierarchical clustering to create a comprehensive perspective … on global development. By clustering countries based on these indicators, the analysis reveals distinct profiles …, offering sustainable development models. MFA and hierarchical clustering have proven effective in categorising countries with …

technique of K-means clustering. When determining the number of clusters, which is especially difficult in the case at hand, we … use an equivalent clustering criterion that is complementary to the squareerror K-means criterion. Our use of this …