## 1 Introduction  
Compared with other steering modes, two hydraulic cylinders arranged symmetrically on a frame has become a major form of steering mechanism for articulated off-road vehicles (AORVs). The frame of an AORV is composed of front frame and rear frame, and the steering of the vehicle is completed by the push and pull of the steering hydraulic cylinders. However, the difference of stroke between two cylinders and the difference arm lead to pressure fluctuation, vibration noise, and a waste of torque during the process of steering [1; 2; 3; 4; 5]. As a reaction to the phenomenon above, scholars and researchers have undertaken many discussions and studies on the optimization of the steering mechanism. [PERSON] [1] analyzed the steering geometry based on two medium-sized domestic loaders by means of quasi-discrete methods; he believed that there was much room for steering mechanism optimization. However, the quasi-discrete method-based optimization results of [PERSON] are not the optimal solution; in other words, there is still much room for improvement. [PERSON] [2] decreased the stroke difference (based on the ZL30 loader) through a sequential unconstrained minimization technique, but the constraints he defined were not clear enough. For example, he put forward that the minimum arm of force depends on the specific structure. Moreover, he did not discuss the impacts of arm difference on steering mechanisms. [PERSON] [3] presented that the stroke difference is proportional to the arm difference; an optimized model was put forward through a geometrical analysis method. In his paper, he did not consider the effects of certain essential factors, such as transmission angle and the actual size of the cylinders. A mathematical model of the cylinder's stroke and arm in the steering process was built by [PERSON] [4], and the mathematical model was optimized based on a matrix laboratory (MATLAB, 2014) optimization toolbox. [PERSON] [5] finished the optimum design for pivot points of steering mechanisms based on the HT25] wheel loader with the optimization toolbox of MATLAB. The parametric design method for the maximum steering torque was obtained by [PERSON] [6], based on the mathematical analysis of the double-cylinder-driven steering mechanism. However, all of the techniques above were solely based on classical analysis and simple geometric logic, thus making optimization and their results unsatisfactory. To address these shortfalls, a genetic algorithm (GA) is presented in this paper as a new method of AORV steering mechanism optimization which has a stronger global search ability for mechanism design. As an evolutionary computation method for optimization, GA works by mimicking biological evolution [7]. A new population is generated through competition, multiplication, and mutation among groups from generation to generation during the solution process, and finally the \"most environment-adapted\" individual is found. Therefore, the global optimal solution is obtained, instead of the local optimal solution [8]. On one hand, the GA method is operated by encoding variables, which ensures that it is not limited by the nature of the variables itself. On the other hand, GA targets groups rather than individuals. Starting with the grouping implies the characteristics of parallel search and global random search, which greatly reduces the possibility of getting an optimal solution. [PERSON] [9] proposed a GA-based design and optimization method for micro-electromechanical systems (MEMS) unimorph piezoelectric energy harvesters, and the GA-based optimization methodology he proposed demonstrated an enhancement of energy harvesting efficiency by 31% in comparison with un-optimized harvesters. This research demonstrated the optimization of micro-electromechanical systems, but only one objective was taken into consideration.