A TOPSIS-BASED ENTROPIC REGULARIZATION APPROACH FOR SOLVING FUZZY MULTI-OBJECTIVE NONLINEAR PROGRAMMING PROBLEMS

Abstract

In this work, a version of the technique fbr order preference by similarity ideal solution (TOPSIS) with entropic regularization approach is developed for solving the fuzzy multi-objective nonlinear programming (MONLP) problems. Applying the basic principle of compromise of TOPSIS, the fuzzy MONLP problem can be reduced into a fuzzy bi-objective nonlinear programming problem. Moreover, following the "tolerance approach," the solution of the fuzzy bi-objective nonlinear programming problem can be obtained by solving a min-max problem. An entropic regularization approach is then applied for solving such a problem. Computational results are provided to illustrate the validity and eficiency of the proposed method.