A new decision-making model for solving multi-objective large-scale programming problems with a block angular structure

This paper presents a model based on a novel compromised solution method to solve the multi-objective large-scale nonlinear programming (MOLSNLP) problems with block angular structure. In this method, an aggregating function that is developed from TOPSIS and VIKOR is proposed based on the particular measure of ‘‘closeness” to the ‘‘ideal” solution. The decomposition algorithm is utilized to reduce the large-dimensional objective space into a two-dimensional space. Furthermore, two independent solution methods are proposed to solve each nonlinear sub problem respectively. In the last step of proposed method, Single objective nonlinear programming problem is solved to find the final solution. Finally, to justify the proposed method, an illustrative example is provided. Then, the sensitivity analysis is described.