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

作　　者：王烜波 李仁旺[1] 

机构地区：[1]浙江理工大学机械工程学院,浙江 杭州

出　　处：《建模与仿真》2024年第1期247-254,共8页Modeling and Simulation

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。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.

关 键 词：机械加工 碳排放 低碳设计 多约束目标优化 

分 类 号：F42[经济管理—产业经济]