An improved branch-and-bound clustering approach for data partitioning

In this paper, we are concerned with clustering algorithms for vertical partitioning. In particular, we examine the use of a branch-and-bound scheme. An existing algorithm using such a scheme may produce infeasible solutions to some problems. We adopt the same branch-and-bound scheme and develop a new branching strategy to avoid infeasibility. Illustrative examples are used to demonstrate the effectiveness of our new approach. In addition, we also show how to formulate the horizontal partitioning problem such that the same algorithm can be applied.