A novel computer-aided design methodology is introduced for synthesizing multicomponent distillation networks. A single-objective unconstrained design problem formulation circumvents numerical challenges regarding lack of robustness and multiple local minima. A thermodynamically motivated temperature collocation approach drastically reduces the number of state variables occurring in rigorous column equilibrium and component balances. A novel chromosome encompassing all column configurations is proposed to solve the mixed-integer nonlinear programming (MILNP) using a stochastic genetic algorithm (GA) with minimum user input. The general formulation and robust performance of the computer-aided design approach naturally extends to multi-component mixtures. Applications include solutions to optimal sequencing problems for up to five species. The massive parallelism of the approach allows for the generation of complete solution maps classifying the design space into regions of optimality. The method also applies to optimal sequences of azeotropic columns. The temperature collocation approach constitutes a promising new design framework for synthesis problems previously not amenable to computer-aided design and analysis. (c) 2005 American Institute of Chemical Engineers