A new approach for fuzzy optimization problem with addition-min composition

This study primarily explores a method of smoothing to address linear objective optimization problems that involve fuzzy relational inequalities with addition-min composition. Due to the concave nature of the constraints, converting such problems into linear programming, which typically involves a convex feasible domain, is challenging. The paper introduces a second-order continuously differentiable function to smooth the constraints and proposes a new approach for solving the problem based on this approximation. It is demonstrated that any cluster of the solution sequence generated by this approach constitutes an optimal solution, and the convergence of optimal values is established. The study includes numerical experiments to demonstrate the performance and effectiveness of the proposed approach. The results indicate that, in comparison to the existing smoothing method, the new approach generally achieves a more accurate solution in terms of both feasibility and optimality

کلیدواژه ها:

Addition-min composition ، fuzzy relation inequality ، optimization.