This paper presents a new Single/Multi-Objective Optimization algorithm inspired by hunting behavior of Grey Wolves (S/MOGWO). Modification is introduced to enhance the convergence rate of GWO. The proposed algorithm has been applied to minimize the emission grades of deleterious pollutants and to reduce the generating cost individually. Also, the proposed MOGWO is used to generate Pareto-optimal solutions for simultaneous minimization of the environmental pollution emissions along with the economic cost. Furthermore, fuzzy decision approach process is implemented to rank and extract the global Pareto-optimal solutions as the most suitable non-dominated solution. The effectiveness of the proposed methodology is tested on IEEE 30-bus system. The generation and security constraints are incorporated into the objective function to achieve a valid and accurate solution. The comparative study with different other techniques confirms the primacy of the proposed algorithm and its potential to solve the OPF problem in single and multi-objective optimization space.