Distillation is the most common industrial separation process. However, simple distillation fails to separate all kinds of mixtures. For instance, when one or more components of a mixture form an azeotrope, it is not possible to fully separate them by simple distillation process. Some modifications are proposed to make the separation of azeotropic mixtures possible. These modifications have resulted methods such as pressure swing distillation, azeotropic distillation, extractive distillation, salt distillation and reactive distillation. The hybrid distillation– pervaporation process can also be utilized for the separation of azeotropic mixtures. Membrane processes show low energy consumption and are environmentally friendly. So, the hybrid distillation–pervaporation process is appropriate for the separation of azeotropic mixtures. The aim of this study was to optimize the hybrid distillation–pervaporation process for the separation of azeotropic mixtures and determine the best arrangement in this process. Most parameters of the process were considered as optimization variables, especially pervaporation parameters such as the number of modules, the permeate pressure and temperature of inlet flow to each module which went unnoticed in previous studies. Reduction of energy costs in a process is a major concern in optimization of hybrid distillation–pervaporation process. In this study, in order to cut energy costs, an efficient method was used for heat integration of the process. To this purpose, heat exchange was provided between all internal streams to the column and inlet streams to pervaporation modules. One of the optimization variables was heat exchange fraction between streams and the number of heat exchangers which was determined by optimization algorithm. In order for the optimization algorithm to have the potential to optimize discrete variables and have a high convergence speed given the high number of optimization variables, genetic algorithm and particle swarm optimization algorithm were utilized. The mentioned cases have been investigated for ETBE production process. To test the efficiency of the proposed method, a comparison was made between the proposed model and other ETBE synthesis processes. To this purpose, 93 ETBE synthesis processes including distillation, reactive distillation, pressure swing distillation, liquid-liquid extraction and pervaporation and a hybrid of these processes were optimized. Results show that the proposed model was selected as the top process (which consists of two reactors, a distillation column, pervaporation unit with series– parallel arrangement, and the hybrid HIDiC, feed splitting and heat integration). It resulted in a 52% TAC reduction compared to the conventional process (which consists of two reactors, two distillation columns, and a liquid-liquid extraction column). Heat integration between internal streams of distillation column and inlet flows to the pervaporation modules resulted in a 20% TAC reduction the most important reason of which was the complete elimination of hot utility pervaporation process. In all hybrid distillation or reactive distillation with pervaporation processes, the best state is when pervaporation process is along with the side stream of the column. In addition, in all hybrid distillation or reactive distillation with pervaporation processes, the series–parallel arrangement between pervaporation modules outperform the series and parallel arrangement the main reason of which is minimized membrane area and utility consumption. The major optimization variables include feed splitting fraction in the feed splitting process, pressure difference of the stripping and rectifying sections in the HIDiC method, heat exchange ratio between streams in heat integration process between internal streams of the column and the inlet flow to pervaporation modules, and the permeate pressure in pervaporation process. In cases when the variables are not optimal, each process may lose its effectiveness.