Global optimization (GO) is aimed at finding the best solution of decision models, in presence of multiple local solutions. GO problems are prevalent in applications described by highly nonlinear system models. Prominent examples include, e.g., the following application areas:
The LGO - abbreviating Lipschitz(-Continuous) Global Optimizer - program system serves to analyse and solve GO problems under very general structural assumptions. It is, hence, particularly suitable to handle GO problems arising from system models supported by limited or difficult-to-use analytical information.
LGO integrates several robust and efficient global and local scope solvers that can be applied in both automatic and interactive modes.
LGO is embedded under a menu-driven user interface, to assist the complete application development process. The visualization capabilities of LGO also serve to help the modeller in finding alternative formulations, and analysing the results.
In the lecture we briefly review the LGO solution approaches, their software implementation, several application areas, and present a software demonstration.
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