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Multi-objective optimization of hydraulic shovel using evolutionary algorithm
Abstract Hydraulic shovel is widely used in mining industry around the world for materials excavation and loading. The mechanical design of hydraulic shovel remains a challenging optimization problem. To address this issue, we establish the many-objective optimization model of a new type hydraulic shovel named TriRocker. An improved reference points-based many-objective differential evolution algorithm is proposed to solve the optimization problem which outperforms twelve state-of-the-art multi-objective and many-objective evolutionary algorithms in the case study. Then the most satisfactory solution is chosen from the obtained non-dominated solutions by a multicriteria decision-making method. Based on the selected solution, a wonderful design of TriRocker hydraulic shovel is obtained. Furthermore, a marketable prototype of 85-ton TriRocker hydraulic shovel is developed by the proposed optimization method. The result demonstrates the feasibility and effectiveness of the many-objective evolutionary algorithm and multicriteria decision-making method in solving the optimization problem of hydraulic shovel.
Highlights The many-objective optimization model of a new type hydraulic shovel named TriRocker is established for the first time. An improved reference points-based many-objective differential evolution algorithm is proposed. First prototype of TriRocker hydraulic mining shovel is developed. MaOEA and MCDM method are successfully applied in the optimization design of hydraulic shovel.
Multi-objective optimization of hydraulic shovel using evolutionary algorithm
Abstract Hydraulic shovel is widely used in mining industry around the world for materials excavation and loading. The mechanical design of hydraulic shovel remains a challenging optimization problem. To address this issue, we establish the many-objective optimization model of a new type hydraulic shovel named TriRocker. An improved reference points-based many-objective differential evolution algorithm is proposed to solve the optimization problem which outperforms twelve state-of-the-art multi-objective and many-objective evolutionary algorithms in the case study. Then the most satisfactory solution is chosen from the obtained non-dominated solutions by a multicriteria decision-making method. Based on the selected solution, a wonderful design of TriRocker hydraulic shovel is obtained. Furthermore, a marketable prototype of 85-ton TriRocker hydraulic shovel is developed by the proposed optimization method. The result demonstrates the feasibility and effectiveness of the many-objective evolutionary algorithm and multicriteria decision-making method in solving the optimization problem of hydraulic shovel.
Highlights The many-objective optimization model of a new type hydraulic shovel named TriRocker is established for the first time. An improved reference points-based many-objective differential evolution algorithm is proposed. First prototype of TriRocker hydraulic mining shovel is developed. MaOEA and MCDM method are successfully applied in the optimization design of hydraulic shovel.
Multi-objective optimization of hydraulic shovel using evolutionary algorithm
Xu, Gongyue (author) / Feng, Zemin (author) / Guo, Erkuo (author) / Cai, Changwang (author) / Ding, Huafeng (author)
2022-07-10
Article (Journal)
Electronic Resource
English
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