Algorithm selection scheduling and configuration of Boolean constraint solvers Boolean constraint solving technology has made tremendous progress over the last decade leading to industrial strength solvers for example in the areas of answer set programming (ASP) the constraint satisfaction problem (CSP) propositional satisfiability (SAT) and satisfiability of quantified Boolean formulas (QBF). However in all these areas there exist multiple solving strategies that work well on different applications; no strategy dominates all other strategies. Therefore no individual solver shows robust state of the art performance in all kinds of applications. Additionally the question arises how to choose a well performing solving strategy for a given application; this is a challenging question even for solver and domain experts. One way to address this issue is the use of portfolio solvers that is a set of different solvers or solver configurations. We present three new automatic portfolio methods: (i) automatic construction of parallel portfolio solvers (ACPP) via algorithm configuration (ii) solving the $NP$ hard…