  Optimization solvers based on methods from constraint programming (OR-Tools,
Chuffed, Gecode), optimization modulo theory (Z3), and mathematical programming
(CPLEX) are successfully applied nowadays to solve many non-trivial examples.
However, for solving the problem of automated deployment in the Cloud of
component-based applications, their computational requirements are huge making
automatic optimization practically impossible with the current general
optimization techniques. To overcome the difficulty, we exploited the sweet
spots of the underlying problem in order to identify search space reduction
methods. We came up with 15 symmetry breaking strategies which we tested in a
static symmetry breaking setting on the solvers enumerated above and on 4
classes of problems. As a result, all symmetry breaking strategies led to
significant improvement of the computational time of all solvers, most notably,
Z3 performed the best compared to the others. As an observation, the symmetry
breaking strategies confirmed that, when applied in a static setting, they may
interact badly with the underlying techniques implemented by the solvers.
