Optimal Design of Hydraulic Excavator Shovel Attachment Based on Multiobjective Evolutionary Algorithm

The optimal design of TriPower shovel attachment remains a challenging task although TriPower face shovel excavators work well in mines all over the world. To address this issue, we establish the multiobjective optimization model of TriPower shovel attachment, which sets three kinematic indicators and two mechanical indicators as the objective functions. An improved multiobjective evolutionary algorithm (MOEA) based on decomposition is proposed to solve the multiobjective optimization problem, which outperforms several representative MOEAs in the case study, and a lot of nondominated solutions are obtained. Then, the most satisfactory solution is selected based on the technique for order of preference by similarity to ideal solution method. Based on this solution, an excellent design of TriPower face shovel excavator is obtained, which can fully realize the three features of TriPower shovel attachment. These results demonstrate the feasibility and effectiveness of the MOEA and multicriteria decision-making method in the optimal design of hydraulic excavator working attachment.