Many industrial problems are concerned with optimization of large and complex systems involving many criteria. Indeed, optimization problems encountered in practice are seldom mono-objective. In general, there are many conflicting objectives to handle. This study introduces a new method for the solution of multi-objective optimization problems. Multi-objective optimization is utilized to find the most suitable solution, which covers the requirements and demands of decision makers. The main goal of the resolution of a multi-objective problem is to obtain a Pareto optimal set and, consequently, the Pareto front. This method is based on the Charged System Search (CSS) algorithm, which is inspired by the Coulomb and Gauss laws of electrostatics in physics. In order to illustrate the efficiency of the proposed method, numerical examples are solved and results are compared to show the ability of the CSS in finding optimal solutions.