Experimental comparison of BTD and intelligent backtracking: Towards an automatic per-instance algorithm selector

Loïc Blet (1) , Samba Ndojh Ndiaye (1) , Christine Solnon (1)

1 M2DisCo - Geometry Processing and Constrained Optimization

We consider a generic binary CSP solver parameterized by high-level design choices, i.e., backtracking mechanisms, constraint propagation levels, and variable ordering heuristics. We experimentally compare 24 different configurations of this generic solver on a benchmark of around a thousand instances. This allows us to understand the complementarity of the different search mechanisms, with an emphasis on Backtracking with Tree Decomposition (BTD). Then, we use a per-instance algorithm selector to automatically select a good solver for each new instance to be solved. We introduce a new strategy for selecting the solvers of the portfolio, which aims at maximizing the number of instances for which the portfolio contains a good solver, independently from a time limit.

Domaines: Informatique [cs]

Loïc Blet, Samba Ndojh Ndiaye, Christine Solnon. Experimental comparison of BTD and intelligent backtracking: Towards an automatic per-instance algorithm selector. International Conference on Principles and Practice of Constraint Programming, Sep 2014, Lyon, France. pp.190-206, ⟨10.1007/978-3-319-10428-7_16⟩. ⟨hal-01301069⟩