Bidirectional branch and bound for controlled variable selection: Part I. Principles and minimum singular value criterion

The minimum singular value (MSV) rule is a useful tool for selecting controlled variables (CVs) from the available measurements. However, the application of the MSV rule to large-scale problems is difficult, as all feasible measurement subsets need to be evaluated to find the optimal solution. In this paper, a new and efficient branch and bound (BAB) method for selection of CVs using the MSV rule is proposed by posing the problem as a subset selection problem. In traditional BAB algorithms for subset selection problems, pruning is performed downwards (gradually decreasing subset size). In this work, the branch pruning is considered in both upward (gradually increasing subset size) and downward directions simultaneously so that the total number of subsets evaluated is reduced dramatically. Furthermore, a novel bidirectional branching strategy to dynamically branch solution trees for subset selection problems is also proposed, which maximizes the number of nodes associated with the bran...

• Type: Journal
• Year: 2008
• Where: CCE
• Authors: Yi Cao, Vinay Kariwala
• Keywords: CCE 2007, CCE 2008, Minimum Singular Value, MSV Rule, Subset Selection Problems