摘要
如何有效地解决计划中的组批问题是铜板带加工首要考虑的问题。在深入研究铜板带生产中订单组批规律的基础上,建立了综合考虑铸锭化学成分、工艺路线以及经济性的多目标组批优化模型,采用一种基于基因段思想的遗传算法,设计了基于基因段的编码、解码、交叉和变异规则,并通过加权因子综合了铸锭个数和工艺路线重合度,将多目标问题转化为单目标进行求解。生产数据试验表明,采用的方法能够减少需要的铸锭数量和中间工序分卷次数,有效地解决了生产中的组批优化问题。
How to tackle the planning order grouping problem effectively became the high priority in copper strip process.Based on the studies of order grouping law in copper strip production,a multi-objective order grouping optimization model was established,which considered ingots＇ chemical constitution,process routing and economic benefits comprehensively.A modified Genetic Algorithm（GA） based on gene segment was proposed,and the rules of coding,decoding,crossover and mutation based on gene segment were designed.The multi-objective problem was converted to single-objective problem to find the solution by integrating the coincidence degree of ingot＇s number and process routing.Production data revealed that the number of copper ingots needed and the times of coil stock dividing in middle process were greatly reduced by using the proposed method,and it could solve the order grouping optimization effectively.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2011年第9期1938-1943,共6页
Computer Integrated Manufacturing Systems
基金
国家863计划资助项目(2008AA04A105)
沈阳市科技计划资助项目(F10-205-1-51)~~
关键词
订单组批
装箱问题
遗传算法
基因段
铜板带
order grouping
bin packing problem
genetic algorithms
gene segment
copper strip
