We propose a mixed-integer nonlinear programming (MINLP) model for simple and complex distillation column design and optimization. The model is based upon the concepts and equations underpinning the McCabe-Thiele method. Generalizing this method, we introduce material balances at various locations of the column and employ binary variables to determine the optimal number of trays and optimal feed locations. We model the vapor-liquid equilibrium using continuous piecewise linear approximating functions. The model is extended to account for multicomponent mixtures and non-constant-molar overflow. We also discuss how to estimate the minimum number of trays and the minimum reflux ratio. 1 | INTRODUCTION Distillation is arguably the most important unit operation in the separation subsystem of chemical processes. The design and optimization of distillation columns have drawn considerable attention in the chemical engineering literature for more than 100 years. A simple yet accurate distillation model is crucial for higher-level modeling such as distillation sequencing, 1-9 separation network synthesis, 10,11 and general process synthesis. 12-14 Methods for modeling distillation columns are discussed in many textbooks 15-17 and review papers. 18-20 In general, there are three types of approaches. First, shortcut methods are frequently used to predict the key design parameters such as minimum reflux ratio, minimum number of trays, and minimum energy demand. Classical shortcut approaches include the Fenske's equation 21 for the minimum number of trays, the Underwood's method 22 for calculating the minimum reflux ratio, and Gilliland's 23 and Smoker's 24 equations for predicting the number of trays. Extending and generalizing the Underwood method, new shortcut procedures were later developed for complex columns 25,26 and batch distillation. 27 Shortcut methods were also proposed to obtain the minimum energy demand for nonideal systems. The boundary value method (BVM) 28 was introduced for homogeneous azeotropic distillation. The rectifying body method (RBM) was proposed for simple 29 and complex 30 distillation columns. Mathematical-programming-based feed angle method (FAM) was developed by Kraemer et al. 31 and later reformulated by Skiborowski et al. 32 to superstructure-based distillation network synthesis. Shortcut methods were also proposed for the design of reactive distillation columns, thermally coupled columns, and divided wall columns. 33-36 Second, rigorous methods are based on material and energy balances and equilibrium calculation for every tray. The enthalpy and vapor-liquid equilibrium (VLE) are described by equations of state (EOS) or thermodynamic models such as UNIQUAC 37 and UNIFAC. 38 The mixed-integer nonlinear programming model by Viswanathan and Grossmann 39 is applicable to predict optimal locations of the feeds and the number of trays required for a distillation column with multiple feeds, which were modified by Smith and Pantelides 40 to allow the feeds to distribute continuously across the column...