基于差分进化–灰狼混合算法的低碳低成本优化模型

Low-Carbon Low-Cost Optimization Model Based on Differential Evolution-Grey Wolf Hybrid Algorithm

摘要: 为了满足碳达峰碳中和需求，单单追求产能效率的机械加工，已经不能满足现代化机械加工产业发展方向的需求。从低能耗和可持续发展角度来看，当前机械设备产品的加工存在提升空间，因此，本文尝试从机械加工制造体系能耗影响因素出发，探讨机械加工钻削工艺优化，以各低碳设计参数改进引起的碳排放和成本双重优化目标，构建关键低碳设计的多约束目标优化模型，并采用差分进化–灰狼混合算法对优化模型进行求解。最后以行星齿轮箱的上端盖为例，验证了文中方法的可行性和有效性。

Abstract: In order to meet the requirements of carbon peak and carbon neutrality, simply pursuing produc-tion efficiency in mechanical equipment processing is no longer sufficient to meet the needs of the modern mechanical processing industry’s development. From the perspective of low energy con-sumption and sustainable development, there is room for improvement in the processing of current mechanical equipment products. Therefore, this paper attempts to explore the optimization of me-chanical drilling processes by considering the factors influencing energy consumption in the me-chanical processing manufacturing system. It aims to achieve a dual optimization objective of re-ducing carbon emissions and costs through improvements in various low-carbon design parameters. To achieve this, a multi-constraint objective optimization model for key low-carbon design is con-structed, and the model is solved using the Differential Evolution-Grey Wolf hybrid algorithm. Fi-nally, taking the upper cover of a planetary gear case as an example, the feasibility and effective-ness of the methods proposed in this paper are validated.