Removing Propagation Redundant Constraints in Redundant Modeling

TL;DR

This paper presents a method to identify and remove propagation redundant constraints in redundant modeling, significantly improving the efficiency of solving constraint satisfaction problems.

Contribution

The paper introduces general theorems for proving propagation redundancy of constraints in redundant models, enhancing solver performance by eliminating unnecessary constraints.

Findings

Removing propagation redundant constraints speeds up solving

Theorems enable systematic detection of redundant constraints

Experimental results on CSPlib problems demonstrate efficiency gains

Abstract

A widely adopted approach to solving constraint satisfaction problems combines systematic tree search with various degrees of constraint propagation for pruning the search space. One common technique to improve the execution efficiency is to add redundant constraints, which are constraints logically implied by others in the problem model. However, some redundant constraints are propagation redundant and hence do not contribute additional propagation information to the constraint solver. Redundant constraints arise naturally in the process of redundant modeling where two models of the same problem are connected and combined through channeling constraints. In this paper, we give general theorems for proving propagation redundancy of one constraint with respect to channeling constraints and constraints in the other model. We illustrate, on problems from CSPlib (http://www.csplib.org/), how detecting and removing propagation redundant constraints in redundant modeling can significantly speed up constraint solving.