Combining finite and continuous solvers

Combining efficiency with reliability within CP systems is one of the main concerns of CP developers. This paper presents a simple and efficient way to connect Choco and Ibex, two CP solvers respectively specialised on finite and continuous domains. This enables to take advantage of the most recent advances of the continuous community within Choco while saving development and maintenance resources, hence ensuring a better software quality.

Improving the Asymmetric TSP by Considering Graph Structure

Recent works on cost based relaxations have improved Constraint Programming (CP) models for the Traveling Salesman Problem (TSP). We provide a short survey over solving asymmetric TSP with CP. Then, we suggest new implied propagators based on general graph properties. We experimentally show that such implied propagators bring robustness to pathological instances and highlight the fact that graph structure can significantly improve search heuristics behavior. Finally, we show that our approach outperforms current state of the art results.