南京航空航天大学学报（英文版）2026，Vol.43Issue(4)：631-652,22.DOI:10.16356/j.1005-1120.2026.04.010
考虑隐性管理约束的滚齿工艺参数多目标优化方法
A Novel Multi-objective Optimization Approach for Gear Hobbing Parameters Considering Hidden Management Constraints
黄伟 1孙笑 2黎小华 3张整新 1陈林1
作者信息
- 1. 航空工业成都飞机工业(集团)有限责任公司,成都 610091,中国
- 2. 武汉科技大学冶金装备及其控制教育部重点实验室,武汉 430081,中国
- 3. 航空工业成都飞机工业(集团)有限责任公司,成都 610091,中国||华中科技大学人工智能与自动化学院,武汉 430074,中国
- 折叠
摘要
Abstract
In the multi-variety and small-batch production mode,the effective historical gear hobbing cases of gear hobbing machine tools represent the best practices under the combined constraints of gear hobbing machine tool,gear,and hob characteristics,as well as gear hobbing management requirements.The gear hobbing parameters of samples in historical gear hobbing cases inherently embed hidden management constraints of gear hobbing.This study established the two-stage multi-objective optimization models for gear hobbing parameters considering hidden management constraints,achieving a trade-off among gear hobbing quality,gear hobbing time,and gear hobbing cost under hidden management constraints.A multi-objective hippopotamus optimization(MHO)algorithm is proposed in this study.The diversity,convergence,and coverage of its Pareto optimal solutions are verified via standard test functions,and the running efficiency of MHO is significantly superior to that of the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)and the multi-objective particle swarm optimization algorithm(MOPSO).By solving the proposed model with MHO,a set of gear hobbing parameters subjected to hidden management constraints is obtained.By designing different selection strategies,multiple optional gear hobbing parameter combinations are provided for technicians.Experimental results show that the effectiveness of gear hobbing using the proposed method meets the requirements of quality,time,and cost subjected to hidden management constraints.The research results are of significant technical and engineering value for technicians and managers to optimize gear hobbing parameters subjected to hidden management constraints.关键词
隐性管理约束/滚齿工艺参数/多目标河马优化算法/非支配排序遗传算法Ⅱ/多目标粒子群优化算法研究亮点:Key words
hidden management constraints/gear hobbing parameters/multi-objective hippopotamus optimization algorithm(MHO)/non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)/multi-objective particle swarm optimi-zation algorithm(MOPSO)分类
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黄伟,孙笑,黎小华,张整新,陈林..考虑隐性管理约束的滚齿工艺参数多目标优化方法[J].南京航空航天大学学报（英文版）,2026,43(4):631-652,22.
