Symmetric Component Caching

Caching, symmetries, and search with decomposition are powerful techniques for pruning the search space of constraint problems. In this paper we present an innovative way of efficiently combining these techniques with branch and bound for solving certain types of constraint optimization problems (COPs). Our new method significantly reduces the overhead of performing decomposition during search when dynamic variable orderings are employed. In addition, it supports the exploitation of dynamic symmetries that appear only during search. Symmetries have not previously been combined with decomposition. Finally, we achieve a superior integration of decomposition and caching with branch and bound than previous approaches. We test our methods on the Maximum Density Still Life problem and show that each of our ideas yields a significant gain in search performance.

• Type: Conference
• Year: 2007
• Where: IJCAI
• Authors: Matthew Kitching, Fahiem Bacchus
• Keywords: Artificial Intelligence, Constraint Optimization Problems, Decomposition, Dynamic Symmetries, IJCAI 2007