An interval valued Pythagorean fuzzy computational algorithm for multiobjective structural problem based on aggregation operators

Many structural problems can be effectively solved by using different standard optimization techniques with well-defined configurations. The design of such optimization problems is associated with imprecise parameters. Therefore, effective design and structural configuration are required to tackle such difficulties. Aggregation operators play a significant role in the decision-making process in aggregating uncertain and vague information. This paper presents Interval-Valued Pythagorean Fuzzy Aggregation Operators (IVPFAOs) to solve Multiobjective Optimization Problems (MOOPs) in structural design. We develop a list of certain models under Interval-Valued Pythagorean Fuzzy Sets (IVPF) using the extension probabilistic operator and the min-bounded sum operator based on the weighted arithmetic mean and the weighted geometric mean. The proposed strategy explores the advantages of IVPFAOs and provides a unique approach to emerging in a decision-making process. Here, we use linear membership and non-membership functions for different objectives under the IVPF environment. We also interpret certain characteristics of our proposed technique. Finally, the effectiveness and practicality of the proposed technique are illustrated using a three-bar truss structural design model. The efficiency of the proposed technique has been explored, and comparative studies with other existing approaches have been conducted. This research contributes to the ongoing efforts to advance the field of evaluation and decision-making by providing novel and effective approaches.

کلیدواژه ها:

Interval Valued Pythagorean Fuzzy Set ، multiobjective structural problem ، Aggregation Operators ، Interval valued Pythagorean fuzzy membership function ، efficient algorithm