The present research attempts to simultaneously optimize the thermal and thermomechanical behavior of a steel ladle lining. The lining configurations are designed with an L32 orthogonal array considering the input parameters of various material properties and lining thicknesses. From the finite-element (FE) simulations, three responses are evaluated: the end temperature and maximum tensile stress at the steel shell and the maximum compressive stress at the hot face of the working lining. Multi-response optimization is performed through grey relational analysis (GRA) and the technique for order preference by similarity to ideal solution (TOPSIS) by applying a distinguishing coefficient of 0.5 in GRA and the signal-to-noise (S/N) ratio-based weight in both techniques. Both GRA and TOPSIS results yield the same best solution (the fourth lining configuration) and the same optimal levels for significant factors. Analysis of variance (ANOVA) is used to identify the significance of the factors and their contributions to the overall performance characteristic. The results demonstrate that the top five factors with the analyses of GRA and TOPSIS are the same and their total contribution is similar.