Application of flexible tolerance genetic algorithm for optimum design of double-crank mechanism

A hybrid method, a flexible tolerance genetic algorithm (FTAGA), is applied in this paper to solve a complicated engineering problem concerning synthesis optimization of a double-crank mechanism. FTAGA is based on the combination of adaptive genetic algorithm (AGA) and flexible tolerance method (FTM) and exploits the advantages of both optimization algorithms. It can efficiently and reliably obtain more accurate global optima for complex, nonlinear, high-dimension, and multimodal optimization problems subject to nonlinear constraints. The successful use of FTAGA for the optimum design of a double-crank mechanism demonstrates that FTAGA is applicable to solve more real-world problems.