Classical Gradient Based Algorithms
Classical gradient based algorithms use the "direction of improvement" information in order to achieve a fast and accurate convergence towards the optimal solution. Well-established mathematical bases guarantee their efficiency.
B-BFGS is a classical gradient based algorithm. Bounded BFGS handles the design variables bounds in a suitable way, while the constraints are efficiently addressed by means of the penalty function method. High accuracy of the solution and high convergence speed are provided.
NLPQLP is a state-of-the-art implementation of Sequential Quadratic Programming algorithm. This single-objective classical gradient base algorithm requires only very few user-provided parameters. Constraints are handled internally in a very efficient way, by means of Lagrange multipliers method.
NBI-NLPQLP is the Normal Boundary Intersection method coupled with the NLPQLP single-objective solver. NBI method applies to any generic smooth multiobjective problem, reducing it to many single-objective constrained subproblems that are efficiently tackled by NLPQLP.