Summary API breaking change: Problem and Solver are now only templated on the matrix type. See the migration guide in the next section. Impact on end-user code is limited, the biggest changes happen in plugin codes. latex/dvips are no longer required for building the documentation. A minimal MathJax will be bundled instead. This explains the larger tarballs. Minor fixes: Fix NumericQuadraticFunction hessian, Fix some alignment issues for 32-bit systems, Fix updateSparseBlock helper function, Fix CachedFunction. Clarify usage of Lagrange multipliers vector λ in Result structure. Add new SolverCallback class to be used with the Multiplexer. Improve printing for several functions. Add jacobian(x) and constraintsOutputSize() methods to Problem. Migration from 3.1 to 3.2 Problem and Solver were templated on the cost function and constraints types, for instance: // Specify the solver type that will be used typedef Solver<DifferentiableFunction, boost::mpl::vector<LinearFunction, DifferentiableFunction> > solver_t; // Deduce the problem type, which is Problem<DifferentiableFunction, boost::mpl::vector<LinearFunction, DifferentiableFunction> > typedef solver_t::problem_t problem_t; Now, this is handled at runtime, and all that remains is the matrix type used: // Specify the solver type that will be used typedef Solver<EigenMatrixDense> solver_t; // Deduce the problem type, which is Problem<EigenMatrixDense> typedef solver_t::problem_t problem_t; The following Problem constructor is now deprecated: // Instantiate the cost function CostFunction cost (param); // Create problem solver_t::problem_t pb (cost); Instead, use the boost::shared_ptr version: // Instantiate the cost function boost::shared_ptr<CostFunction> f (new CostFunction (param)); // Create problem solver_t::problem_t pb (cost); Flags are now used to identify a function's "true" type at runtime. For instance: // f is a (shared) pointer to a function, and we want to cast it to a LinearFunction // if that is possible LinearFunction* g = 0; if (f->asType<LinearFunction> ()) { g = f->castInto<LinearFunction> (); } The implementation thus relies on a cheap static_cast rather than an expensive dynamic_cast. Note that castInto accepts a boolean parameter to enable the asType check internally, and throw if the cast is invalid.