Changes in environmental regulations have often resulted in the need to replace existing solvents with more environmentally benign substitutes. For example, solvents such as 1,1,1, trichloroethane are being phased out within the next few years. In general, ＇designer＇ compounds, which have desired properties, can be obtained with the help of computer-aided molecular design (CAMD) approaches. In recent years, the above product design problem has often been posed as a mathematical programming problem. In this framework, the desired attributes of the compound are posed as performance objective and constraint functions. Nonlinear functions, such as those associated with solubility parameter models seen in solvent design, can lead to multiple local solutions (i.e. optimization minima). For these cases, the failure to design the globally optimal compound (using a local optimization approach) can introduce a source of uncertainty. Thus, there is a need for global optimization techniques in product design. To address this need, we have developed a new global optimization algorithm that exploits the structure of the CAMD formulation. We have used this algorithm to study the design of environmentally benign solvents for surface cleaning applications in the printing industry.