LIPIcs.ICLP.2012.176.pdf
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Although Boolean Constraint Technology has made tremendous progress over the last decade, it suffers from a great sensitivity to search configuration. This problem was impressively counterbalanced at the 2011 SAT Competition by the rather simple approach of ppfolio relying on a handmade, uniform and unordered solver schedule. Inspired by this, we take advantage of the modeling and solving capacities of ASP to automatically determine more refined, that is, non-uniform and ordered solver schedules from existing benchmarking data. We begin by formulating the determination of such schedules as multi-criteria optimization problems and provide corresponding ASP encodings. The resulting encodings are easily customizable for different settings and the computation of optimum schedules can mostly be done in the blink of an eye, even when dealing with large runtime data sets stemming from many solvers on hundreds to thousands of instances. Also, its high customizability made it easy to generate even parallel schedules for multi-core machines.
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