Complex crank-slider mechanism dynamic balancing by Binary Genetic Algorithm(BGA)

The present article describes the application of Genetic Algorithm for force and moment balancing of a crank-slider mechanism. This technique permits competing design objectives to be considered through the investigation of trade-offs between those objectives. The objective functions of the design parameters are determined and their values are minimized by adjusting the independent variables of the designer and the limitation of design. The technique permits both partial force and moment balancing to be accomplished simultaneously while the desired constraints are satisfied. In this case, we minimize the forces with regard to the constraints of the moments using Genetic algorithm (GA). One of the proper types of GA is Binary Genetic Algorithm (BGA) that uses the chromosomes as binary codes. Therefore, in presented paper, BGA is selected to have good trade-off between the answers accuracy and convergence speed.