Simulation and optimization of multiphase distillation are often required in the design and operation of process plants. In this work, a simultaneous solution method (tau-method) is proposed and studied for simulating/optimizing two-and three-phase distillation. This method involves modification of mole fraction summations such that the same set of governing equations is valid for different phase regions, and hence phase identification and solution of the governing equations can be performed simultaneously and effectively. The optimization problem involved in the tau-method has a linear objective function and nonlinear constraints, and it can be solved using an iterated linear programming (ILP) or nonlinear programming (NLP) approach. The tau-method is applied to steady state simulation and optimization of two- and three-phase distillation. The results obtained for several examples and conditions are shown to be consistent and comparable to those in the literature. The tau-method is successful for simultaneous simulation and optimization of multiphase distillation. For the distillation examples tried by the tau-method with the ILP approach, initialization based on feed is often satisfactory, major iterations (similar to those in Newton method) for convergence is 5 to 10, and CPU time on a personal computer is less than 1 minute. On the other hand, the tau-method with the NLP approach generally requires better initialization and/or more computations for convergence.