Experimental studies of variable selection strategies based on constraint weights

An important class of heuristics for constraint satisfaction problems works by sampling information during search in order to inform subsequent decisions. One of these strategies, called the "weighted degree heuristic", is based on weighting constraints according to their involvement in failure during search. Recently, a new approach to sampling based on weighted degree was introduced, that uses a form of "random probing" to gain information that is less subject to sampling bias. This approach also involves restarting in order to enhance the initial choices made during search. The present research analyses the characteristics of the sampling process and the manner in which information is used, to better understand strategies based on constraint weights. Using a framework based on two performance principles, the well-known Fail-First and a "Contention Principle", we study the properties of both the sampling and variable selection components. We show that th...

• Type: Journal
• Year: 2008
• Where: JAL
• Authors: Richard J. Wallace, Diarmuid Grimes
• Keywords: Constraint Satisfaction Problems, Heuristic, JAL 2008, Weighted Degree