Optimal Rectangle Packing: A Meta-CSP Approach

We present a new approach to optimal rectangle packing, an NP-complete problem that can be used to model many simple scheduling tasks. Recent attempts at incorporating artificial intelligence search techniques to the problem of rectangle packing have focused on a CSP formulation, in which partial assignments are defined to be the fixed placement of a subset of rectangles. Our technique takes a significant departure from this search space, as we instead view partial assignments as subsets of relative pairwise relationships between rectangles. This approach recalls the meta-CSP commonly constructed in constraint-based temporal reasoning, and is thus a candidate for several pruning techniques that have been developed in that field. We apply these to the domain of rectangle packing, and develop a suite of new techniques that exploit both the symmetry and geometry present in this particular domain. We then provide experimental results demonstrating that our approach performs competitively ...

• Type: Conference
• Year: 2006
• Where: AIPS
• Authors: Michael D. Moffitt, Martha E. Pollack
• Keywords: AIPS 2006, Artificial Intelligence, Optimal Rectangle, Partial Assignments, Rectangle Packing