In the present study, a multi-objective approach is proposed to find optimum operating condition of natural gas network. For this purpose, a thermodynamic modeling of natural gas through the main elements of the network i.e. pipelines and compressor stations (CSs) is performed. This study aims to find optimum values of three conflicting objective functions namely maximum gas delivery flow and line pack, and minimum operating cost (sum of fuel consumption and carbon dioxide emission costs), simultaneously. Here, fast and elitist non-dominated sorting genetic-algorithm (NSGA-II) is applied by considering fourteen decision variables: number of running turbo-compressors (TCs) and rotational speed of them in compressor stations as well as gas flow rate and pressure at injection points. The results of multi-objective optimization are obtained as a set of multiple optimum solutions, called 'the Pareto optimal solutions'. Furthermore, a set of typical constraints, governing the pipeline operation, is subjected to obtain more practical solutions. To control the constraints satisfaction and to find better solutions in optimization process, the penalty functions are defined and applied. Sensitivity analysis of change in the objective functions, when the optimum decision variables vary, is also conducted and the degree of each parameter on conflicting objective functions is investigated. (C) 2014 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.