This work aims at proposing a multi-objective optimization (MOO) strategy for dividing wall column (DWC) that can provide energy-efficient and cost-effective operation for ternary feed mixtures compared to its conventional two-column distillation sequence. Today, DWC has emerged as a promising industrially relevant thermally integrated configuration. If its design and operating conditions are truly optimized, the cost can further be reduced. At the same time, it is also equally, if not more, important for a distillation column to consider its product purity, productivity and environmental standard. With this, a multi-objective genetic algorithm based optimization framework is formulated to include all these crucial factors. Due to the presence of various conflicting objectives, multiple optimal solutions are inevitable. With this, the proposed optimization strategy works with the three steps: (i) sensitivity analysis to find the decision variables, (ii) a non-dominated sorting genetic algorithm (NSGA-II) to generate multiple optimal solutions, and (iii) the technique for order of preference by similarity to an ideal solution (TOPSIS) method to select one optimal point. Further, the Aspen Plus flowsheet simulator is integrated with MATLAB to simultaneously perform extensive simulation and optimization. This potential integration leads to reducing the total run time substantially. Finally, two industrially relevant ternary systems, namely Benzene-Toluene-Xylene (BTX) and Benzene-Toluene-Ethylbenzene (BTE) are used to illustrate the proposed strategy for investigating the performance improvement of the DWC over its conventional distillation sequence (CDS). Simulation results show that the DWC can secure up to 23% savings in capital cost, 45% in operating cost and reduce the rate of carbon dioxide emission by about 45%.