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This paper devises a multi-objective cost function which elaborates different constraints as well as an optimality criterion for design of serial robotic manipulators. In practice, inclusion of different constraints drastically limits the possible range of design parameters. The result of minimizing this multi-objective cost function is compared with another method which locates an optimal solution using a graphical representation. The effectiveness of the proposed cost function is demonstrated by a unified solution for both methods. In addition, possible tolerance of design parameters is compensated by considering a neighborhood around these parameters. Through an illustrative example, it is shown that the inclusiveness and flexibility of the proposed method makes it suitable for geometric design optimization of robotic manipulators.