MultiGLODS: Global and Local Multiobjective Optimization using Direct Search

 

A solver for global multiobjective

derivative-free optimization

 

The optimization of multimodal functions is a challenging task, in particular when derivatives are not available for use. MultiGLODS is a solver suited for global multiobjective constrained optimization which does not use any derivatives of the objective functions.

 

Using direct search of directional type, the algorithm alternates between a search step, where potentially good regions are located, and a poll step where the previously located promising regions are explored. Components of the objective function are not aggregated and new points are accepted using the concept of Pareto dominance. The initialized searches are not all conducted until the end, merging when start to be close to each other, this way keeping affordable computational budgets in terms of number of functions evaluations.

 

In the end of the optimization process, the set of all active points will define the approximations to the Pareto fronts of the problem (local and global).

MultiGLODS is freely available for research, educational or commercial use, under a GNU lesser general public license.

References and complementary material:


The MultiGLODS team:
Ana Luísa Custódio (Universidade Nova de Lisboa)
José F. Aguilar Madeira (ISEL and IDMEC-IST, Lisbon)