A novel binomial-based fuzzy type-2 approach for topology and size optimization of skeletal structures

Abstract

The current work introduces a new probability-based fuzzy type-2 decision mechanism to adjust the optimization process during the simultaneous size and topology optimization of the Skeletal structural systems. For the probabilistic part a binomial module is developed that feeds the fuzzy mechanism by forecasting success probability for future topological actions. The proposed fuzzy decision mechanism permanently monitors the optimization process and attends to dynamically tune the balance between size and topology actions. The presented strategy, by reducing the number of ineffective iterations, significantly enhances the efficiency of the optimization process. Since the proposed decision mechanism is designed as an auxiliary separate module it can be integrated with different optimization methods. Accordingly, in this study, it is integrated with four different optimization algorithms and applied to solve distinct size and topology problems. To comprehensively evaluate the effect of the proposed strategy a new performance index is defined and employed. The acquired results demonstrate that the proposed decision mechanism considerably enhances the search performance of the algorithms on handling the structural size and topology optimization problems.