云制造模式下粤港澳大湾区供应链的调度优化问题研究  

Research on Scheduling Optimization of Supply Chain in Guangdong-Hong Kong-Macao Greater Bay Area under Cloud Manufacturing Mode

作　　者：林子楚 施婉思 郑思妙 白敏静 杜倩怡 刘念[1] 张元阳 巫秋仪 LIN Zi-chu;SHI Wan-si;ZHENG Si-miao;BAI Min-jing;DU Qian-yi;LIU Nian;ZHANG Yuan-yang;WU Qiu-yi(South China Normal University,Guangzhou 528225,China)

机构地区：[1]华南师范大学,广州528225

出　　处：《价值工程》2020年第36期92-95,共4页Value Engineering

基　　金：2020年广东大学生科技创新培育专项资金(“攀登计划”专项资金)项目,项目编号:pdjh2020b0168;课题项目:广州市哲学社科规划2020年度课题,课题编号:2020GZGJ62。

摘　　要：将粤港澳大湾区建设成为世界现代服务业基地是粤港澳大湾区发展的重点之一,而供应链是提供服务的基础,提高其能力和效率,才能保障服务的质量。随着云制造这种新型制造服务模式的发展,该模式下的供应链调度优化已经成为当今制造业研究的热点。利用遗传算法和蚁群优化的混合算法来解决云制造供应链调度优化问题,相较于传统的优化运算而言,该混合运算结合了不同算法和模型之间的优点,具有独特的优势。To build Guangdong-Hong Kong-Macao Greater Bay Area into the world's modern service industry base is one of the key points in the development of Guangdong-Hong Kong-Macao Greater Bay Area,and the supply chain is the basis of providing services.Only by improving its ability and efficiency can the quality of services be guaranteed.With the development of cloud manufacturing as a new manufacturing service mode,the optimization of supply chain scheduling under this mode has become a hot topic in manufacturing research.The hybrid algorithm of genetic algorithm and ant colony optimization is used to solve the scheduling optimization problem of cloud manufacturing supply chain.Compared with the traditional optimization algorithm,the hybrid algorithm combines the advantages of different algorithms and models and has unique advantages.

关 键 词：供应链调度 云制造 蚁群算法 遗传算法 

分 类 号：F259.27[经济管理—国民经济]