Computational global optimization:: Models, algorithms and applications

The objective of global optimization (GO) is to find the absolutely best solution of constrained nonlinear decision models that often have multiple-local and global-optima. We present a review of the most frequently used GO models and solution strategies, highlighting also issues in software development. Next, the principal features of LGO-an integrated model development and solver system for analyzing GO problems-are discussed. For illustration, a variety of important applications are listed with further pointers towards the rapidly increasing body of GO literature.