基于改进NSGA-II算法的制造企业供应链系统优化  

Supply chain system optimization of manufacturing enterprise based on improved NSGA-II algorithm

在线阅读下载全文

作  者:关颜慧 李军星 贾现召[1] GUAN Yanhui;LI Junxing;JIA Xianzhao(School of Mechatronics Engineering,Henan University of Science and Technology,Luoyang 471003,China)

机构地区:[1]河南科技大学机电工程学院,河南洛阳471003

出  处:《河南科技学院学报(自然科学版)》2024年第6期69-80,共12页Journal of Henan Institute of Science and Technology(Natural Science Edition)

基  金:国家自然科学基金(52005159);河南省科技攻关项目(222102220061);河南省高校青年骨干教师培养计划(2021GGJS048)。

摘  要:在对制造企业进行供应链系统的优化过程中,针对系统的经济性、稳定性和消费者满意度之间存在的优化冲突问题,结合制造企业供应链系统的运行特性,对由供应商、制造商、零售商和分销商所组成的四级供应链系统体系进行研究,实现以供应链系统的利润最大、稳定性最高和消费者满意度最大为核心目标建立多目标优化模型.结合企业具体算例,通过引入矩阵实数编码、邻域搜索算子和动态拥挤距离的多样性保持策略对NSGA-II算法进行改进.利用MATLAB软件对制造企业供应链系统可靠性优化模型进行仿真验证.结果证明本方法能有效提高制造企业供应链系统的优化能力,从而为企业在竞争激烈的市场中实现供应链的高效管理和运营提供参考.Aiming at the conflicts of economy,consumer loyalty and stability in the process of supply chain system optimization of large manufacturing enterprises,Based on the actual situation of the supply chain system of manufacturing enterprises,this paper studies the four-level supply chain system consisting of suppliers,manufacturers,retailers and distributors,and establishes a multi-objective optimization model with the aim of maximizing profit,stability and consumer satisfaction.The algorithm NSGA-II is improved by introducing matrix real number coding,neighborhood search operator and dynamic crowding distance diversity preserving strategy.The reliability optimization model of supply chain system of manufacturing enterprise is simulated and verified by MATLAB software.It is proved that this method can improve the optimization ability of supply chain system of manufacturing enterprises,and support enterprises to realize efficient management and operation of supply chain in the competitive market.

关 键 词:供应链 多目标优化 改进的NSGA-II算法 

分 类 号:TP277[自动化与计算机技术—检测技术与自动化装置] TB498[自动化与计算机技术—控制科学与工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象