摘要
为制定网络化制造(networked manufacturing,NM)模式下供应链合作成员间的动态调度策略,构建了由制造商、协同设计商以及客户组成的三层动态调度模型;在生产能力约束、多目标优化约束等制约因素下,采用时间函数、成本函数和延期惩罚函数三个目标函数对调度问题进行描述;使用改进蚁群算法(improved ant colony optimization algorithm,IM-ACO),对调度路径可行解节点添加不同的信息素,并将信息素浓度约束在τ_(min)和τ_(max)之间,使得供应链客户个性化需求服务、运作时间、成本等综合收益达到最优.实例仿真表明本文提出的动态调度优化算法求解具有较快的搜索速度、收敛性好,算法具有较好的稳定性;同时,也表明本文构建调度模型合理,可以为实际生产调度提供优化的策略.
In order to get dynamic scheduling strategy of alliance members based on networked manu- facturing （NM）, we set a three-layer dynamic scheduling model composed of manufacturer, cooperative designer and customer. Under the constraints of product capability and multi objective optimization, we apply three objective functions： time function, cost function and delay punishment function to depict the scheduling model. In addition, an improved ant colony optimization algorithm （IM-ACO） is employed to solve our presented model. By adding different pheromone concentration to the feasible nodes of scheduling path, we confine pheromone concentration within Train and Tm~~, thus get optimal benefits regarding indi- vidual service of customer, operation time, and cost. An actual case experiment shows that the presented optimization algorithm has fast search speed, better convergence, and good stability. Furthermore, it also proves our designed scheduling model is reasonable, which can provide optimal strategy for real-world scheduling.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2014年第5期1267-1275,共9页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(71201106
71301108)
中国博士后科学基金(2013M530228)
辽宁省博士启动基金(20111052)
关键词
供应链动态调度
改进蚁群优化算法
网络化制造
信息素
多约束
supply chain dynamic scheduling
improved ant colony optimization algorithm
networkedmanufacturing
pheromone
multi-constraint
