Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …

Data analysis plays an indispensable role for understanding various phenomena. Cluster
analysis, primitive exploration with little or no prior knowledge, consists of research …

The monograph Data Clustering: Theory, Algorithms, and Applications was published in
2007. Starting with the common ground and knowledge for data clustering, the monograph …

Systematic change of neighborhood within a local search algorithm yields a simple and
effective metaheuristic for combinatorial optimization. We present a basic scheme for this …

This paper introduces time‐varying grouped patterns of heterogeneity in linear panel data
models. A distinctive feature of our approach is that group membership is left unrestricted …

This chapter characterises the scope of this book. It explains the reasons why one should be
interested in cluster analysis, lists major application areas, basic theoretical and practical …

The importance of high performance algorithms for tackling difficult optimization problems
cannot be understated, and in many cases the only available methods are metaheuristics …

Systematic change of neighborhood within a possibly randomized local search algorithm
yields a simple and effective metaheuristic for combinatorial and global optimization, called …

This is the first book to take a truly comprehensive look at clustering. It begins with an
introduction to cluster analysis and goes on to explore: proximity measures; hierarchical …

Variable neighborhood search (VNS) is a metaheuristic for solving combinatorial and global
optimization problems whose basic idea is a systematic change of neighborhood both within …