Global optimization is a multi-disciplinary research field that deals with the characterization and computation of global minima and/or maxima of nonlinear, nonconvex, nonsmooth and discrete functions. Global optimization problems are frequently encountered in modeling real world systems for a very broad range of applications including aerospace and civil engineering, chemical and process engineering, computational biology and bioinformatics, computational materials science, clustering and pattern recognition, computer vision and robotics, cryptography and data mining, electrical and control engineering, information and technology management, industrial and systems engineering, communication and information network design, intelligent information and security, management science and operations research, mathematical economics and financial engineering, mechanical and structural engineering, neuroscience and cognition, refining and petrochemicals, reliability and quality engineering, signal and image processing, tomography and seismic optimization, production planning and scheduling, transportation and logistics, etc. With the rapid development and deployment of practical global optimization methodologies in the last thirty years, more and more scientists in diverse disciplines have been using global optimization techniques and algorithms to solve their respective problems. Global optimization is playing a pivoting role in the development of modern engineering and sciences. The field has become mature enough to call for the establishment of a world congress.