The design of mixtures plays an important role in improving process and product performance
but is challenging because it requires finding the optimal number, identities and compositions of
mixture components and using nonlinear property models. To address this, a general modeling
framework for mixture design problems is presented. It integrates Generalized Disjunctive Programming
(GDP) into Computer-Aided Mixture/blend Design via Hull Reformulation (HR). The
design methodology is applied successfully to a case study involving solid-liquid equilibrium calculations
to find an optimal solvent mixture that dissolves ibuprofen. The results show that the
proposed GDP-based approach appears very promising for the design of mixture problems. The
HR approach is used to solve mixture problems successfully. Its overall computational efficiency
is found to be better than that of Big-M approach. Numerical difficulties arising from the absence
of components in the final mixture can be avoided, leading to computationally efficient solutions.