Simultaneous optimization of process flowsheets using equation-oriented (EO) methods is a promising alternative to simulation studies. With the use of EO methods, simultaneous optimization of all process units including heat integration can be performed to achieve goals such as maximizing profit or minimizing operating costs. The use of EO methods required the development of new process models and equations of state (EOS), as algorithms and some formulations used in sequential methods do not work in an EO environment. Advancements in EO methods, along with the growth of gradient-based solvers, have enabled large-scale simultaneous flowsheet optimization. However, simultaneous process optimization still faces challenges as large problems, especially non-linear ones, may not achieve convergence without good initial values. A study on the simultaneous optimization of the integrated gasification and combined cycle (IGCC) process using EO methods was conducted as it is a combination of a cryogenic air separation unit (ASU), a coal gasifier and power generation units consisting of a combustor, a gas turbine, a heat recovery steam generator (HRSG) and a steam turbine. The purity of the oxygen product fed to the gasifier was often considered to be fixed in prior IGCC studies. With the ASU model and gasifier model used, the influence of oxygen purity and flowrate fed to the gasifier can be studied. The thermal efficiency of the IGCC process was maximized in GAMS using full-order EO process models. After the optimization, the thermal efficiency increased from 27.7 % in the base case to 36.7 %, with a notable change in process parameters, showing that the solver did not terminate close to the starting solution. Results showed that lowering the oxygen product purity from 95 % to 58.6 % increased the thermal efficiency of the IGCC process as the power required by the compressor in the ASU was reduced.