GOT solves practical problems in a stand-along mode or work together with effective meta-heuristic methods, and amenable to parallel implementation.
GOT has developed a variety of very powerful methods, such as TRUST-TECH-guided interior point method, TRUST-TECH-guided branch-and-bound methods, TRUST-TECH guided evolutionary algorithms (PSO, GA, DE, etc.).
From the function and application viewpoint, it achieves the following:
Finds the global optimal solution in a deterministic and relatively fast manner.
Finds a set of local optimal solutions in a fast manner and avoids revisiting local optimal solutions.
Solves general optimization problems and highly difficult problems (enabling technology).
Diagnoses divergent and infeasible optimization problems.
Is easy and straightforward to interface with any local and/or global method to quickly find the global optimal solution.
Provides multiple local optimal solutions with respect to varying objectives.
From a user’s viewpoint, it offers the following much-wanted features:
Users can continue to use the existing computer program and operate their current graphical user interface (GUI) (No new learning curve or surpass the old degree of faith).
A better, if not the best, programming environment for maintaining and updating global methods for finding high-quality local optimal solutions.
Users can quickly obtain better, if not the best results.