%0 Journal Article %T 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 %A 王烜波 %A 李仁旺 %J Modeling and Simulation %P 247-254 %@ 2324-870X %D 2024 %I Hans Publishing %R 10.12677/MOS.2024.131024 %X 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. %K 机械加工,碳排放,低碳设计,多约束目标优化
Mechanical Processing %K Carbon Emissions %K Low-Carbon Design %K Multi-Constraint Objective Optimization %U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=79117