摘要
基于国内大型钢铁企业中钢管生产的实际,将无缝钢管的生产计划调度抽象为多目标柔性Job-shop问题(MFJSSP).在考虑产线产能各不相同、产线定修、前置库存限制的情形下,构建了混合整数规划模型,解决①多产线共存情形下的生产路径柔性选择;②以订单的按时完工、各订单的供料尽量连续、规格转换成本最小为目标的多目标生产调度优化.鉴于该问题的NP-hard性,设计改进的遗传算法进行求解,该模型和算法已被用于无缝钢管冷区生产作业计划软件系统的开发,并在实际运用中取得了良好的效果,对各大钢管企业的生产调度均具有一定的实际指导意义.
Based on the distinct characteristics of steel tube production process, the production plan and scheduling problem of seamless steel tubes is described as Multi-Objective Flexible Job-Shop Scheduling Problem. Considering the parallel machines of different capacities and speeds environments, maintenance of machines as well as inventory restriction, it is formulated as mixed-integer-programming model to （1） decide the flexible routes for every job （2） optimize the planning and scheduling, whose objective is not only to meet delivery date, but also to minimize transform cost and interruption in production. Given the problem is NP-hard, improved genetic algorithm is suggested, whose effectiveness can be well verified in scheduling decision support system for the production of seamless steel tubes of real company .
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2009年第8期117-126,共10页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(70832005)
上海市科委重点攻关项目(06JC14064)
上海市重点学科建设项目(B310)
同济大学面向二十一世纪教育振兴行动计划-供应链与工业工程研究实验室建设项目
关键词
无缝钢管
多目标柔性Job-shop问题
混合整数规划模型
遗传算法
生产调度
seamless steel tube
multi-objective flexible Job-shop scheduling problem
mixed- integerprogramming model
genetic algorithm
planning and scheduling
