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Speedups Achieved

Although ParamILS can in principle optimize arbitrary user-defined objective functions, so far, it has achieved its greatest successes in minimizing the runtime algorithms require to solve a given problem. For doing so effectively, ParamILS relies on the idea of ``adaptive capping'', introduced in the ParamILS JAIR article.

Problem Domain Algorithm(s) Speedups over default Citation
Propositional Satisfiability SPEAR 4.5-500 [Hutter at al., FMCAD '07]
SAPS 8.1-130 [Hutter et al., AAAI '07]
SATENSTEIN 1.6-2.8 [KhudaBukhsh et al, IJCAI '09]
Captain Jack
Mixed Integer Programming CPLEX 2.0-52 [Hutter et al., CPAIOR '10]
GUROBI 1.2-2.3 [Hutter et al., CPAIOR '10]
LPSOLVE 1.0 1.0-153 [Hutter et al., CPAIOR '10]
Timetabling UBCTT >28 [Fawcett et al., Tech Report '09]
AI Planning FASTDOWNWARD 1.0-23 [Fawcett et al., ICAPS-PAL '11]
LPG 3.0-118 [Vallati et al., ICAPS-PAL '11]
Most probable explanation GLS+ >360 [Hutter et al., AAAI '07]
Protein folding REMC 1.2-3.0 [Thachuk et al., BMC Bioinformatics '07]