Solver4J – Algorithm Examples

Convex optimization

Depending on the type of the (convex) problem it has to be solved, you have to choose the right method of solution. Solver4J comes with a complete set of algorithms that can be used to address a given convex minimization: you can engage directly one of them (see "Convex Optimization" for an in-depth reference), or simply invoke Solver4J that will take the choice for you. As regards the two proposed interior-point methods, they are mutually exclusives: default is the primal-dual method, but you can freely specify the barrier method in your optimization request.

Newton unconstrained
Newton linear equality constraints with feasible starting point
Newton linear equality constraints with infeasible starting point
barrier interior-point method
primal-dual interior-point method
all-in-one (Solver4J)

Algorithm examples

Convex optimization