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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 ofcomponent-based applications, their computational requirements are huge makingautomatic optimization practically impossible with the current generaloptimization techniques. To overcome the difficulty, we exploited the sweetspots of the underlying problem in order to identify search space reductionmethods. We came up with 15 symmetry breaking strategies which we tested in astatic symmetry breaking setting on the solvers enumerated above and on 4classes of problems. As a result, all symmetry breaking strategies led tosignificant improvement of the computational time of all solvers, most notably,Z3 performed the best compared to the others. As an observation, the symmetrybreaking strategies confirmed that, when applied in a static setting, they mayinteract badly with the underlying techniques implemented by the solvers.

Benchmarking Optimization Solvers and Symmetry Breakers for the  Automated Deployment of Component-based Applications in the Cloud (EXTENDED  ABSTRACT)