During the recent decade, meta-heuristic algorithms have been developed by researchers for structural optimization. Multiobjective optimization aims at finding a trade-off between objective functions. In this paper, Teaching-Learning-Base Optimization (TLBO) algorithm is developed for multiobjective optimization of steel frames, called Non-dominated Sorting Teaching-Learning-Based Optimization (NSTLBO) algorithm. To evaluate the efficiency of the algorithm, five benchmark steel frames including three moment resisting frame and two braced frames are optimized using NSTLBO. The weight of the structure and the maximum displacement are considered as the objective functions to be minimized. Sizes of the elements are employed as design variables. The structures analyzed using a developed code in MATLAB, and designed according to the AISC-LRFD specifications. Results including trade-off between the objective functions showed the efficiency of the algorithm.