基于改进白鲸优化算法的低碳柔性工艺规划  

Low-carbon flexible process planning based on improved beluga whale optimization algorithm

作　　者：孔云 周学良 冷杰武 KONG Yun;ZHOU Xueliang;LENG Jiewu(School of Mechanical Engineering,Hubei University of Automotive Technology,Shiyan 442002,China;School of Electromechanical Engineering,Guangdong University of Technology,Guangzhou 510006,China)

机构地区：[1]湖北汽车工业学院机械工程学院,十堰442002 [2]广东工业大学机电工程学院,广州510006

出　　处：《现代制造工程》2024年第1期80-88,共9页Modern Manufacturing Engineering

基　　金：国家自然科学基金资助项目(52075107);湖北省高等学校优秀中青年科技创新团队计划项目(T2020018)。

摘　　要：针对数控加工过程的低碳柔性工艺规划问题,建立了以加工过程中机床、刀具和装夹的转换次数和碳排放为目标的优化模型,提出了基于改进白鲸优化算法的求解方法。该算法通过引入变异操作增强其全局搜索能力,并在种群初始化中采用以加工资源为导向的启发式规则选择策略与随机生成相结合的方式,以提高初始种群的质量,加快算法的收敛速度。最后,以一个零件的加工信息为测试实例,验证所提模型的可行性,并与其他3种算法进行对比。试验结果表明,所提出的算法能够获得更优解,且具有更快的收敛速度。Aiming at the low-carbon flexible process planning problem of CNC machining process,an optimization model aiming at the conversion times of machine tools,tools and clamping and carbon emissions in the machining process was established,and a solution method based on the improved beluga whale optimization algorithm was proposed.The algorithm enhances its global search ability by introducing mutation operations,and adopts a heuristic rule selection strategy oriented to processing resources combined with random generation in population initialization to improve the quality of the initial population and accelerates the convergence speed of the algorithm.Finally,taking the machining information of a part as a test example,the feasibility of the proposed model was verified,and compared with the other three algorithms.The experimental results show that the proposed algorithm can obtain a better solution and has a faster convergence speed.

关 键 词：柔性工艺规划 碳排放 转换次数 白鲸优化算法 

分 类 号：TH162[机械工程—机械制造及自动化]