There are two most common methods to deal with multi-objective optimization problems, transforming into single-objective optimization problems by aggregation function, or directly solving them using multi-objective evolutionary algorithm. For a long time, there is a lack of quantitative comparative studies for these two approaches in the optimal design of hydraulic excavator. To address this issue, the multiobjective optimization model of hydraulic excavator with ordinary shovel excavation mechanism was firstly established, which set level crowding, digging forces, crowding force and the indicator of digging atlas as objective functions. Then, twelve representative evolutionary algorithms which contained six single-objective evolutionary algorithms and six multi-objective evolutionary algorithms were applied in the optimal case of 70-ton hydraulic excavator. The performance metrics of single-objective optimization and multi-objective optimization were all considered for the comparison. The result shows that multi-objective evolutionary algorithms are significantly superior to single-objective evolutionary algorithms and proved to be the more suitable choice for multi-objective optimization problems, which can provide more quality and balanced solutions for designer.