暂存区受限瓦楞纸板生产线下料问题研究

Study for Normal Paperboard Cutting Stock Problem with Constraints of Temporary Buffers

针对当前高速瓦楞纸板全自动生产线在生产多品种、大批量纸板订单时,存在原材料损耗大、各生产流程协同性差等问题,课题组提出一种瓦楞纸板生产全流程集成优化方法。在瓦楞纸板下料的基础上,提炼出一类受暂存区存储规则强顺序约束的一般纸板排样下料问题;模型以原料使用量最小为优化目标,综合决策图案排样及其顺序,将问题简化为3种关键变量的组合优化;基于模型强约束特征,设计通过"排样池"交互的2层嵌套算法,上层采用遗传算法决策订单放入排样池的顺序,下层设计基于"条带截断启发式规则"的2阶段确切算法决策图案构造。实验结果表明:该算法可以有效地约减低质量解空间,具备高寻优能力和求解稳定性。

Aiming at the the large raw material loss,poor coordination of various production processes and other problems in high-speed automatic production line of corrugated cardboard when producing tasks of many species and large demands,an integrated optimization method for the whole production process of corrugated cardboard was proposed.A general problem of coil cutting for paperboard which was coercive constrained by temporary buffers was proposed based on the studies of corrugated board production.Then a mathematic model was constructed by taking the minimum amount of raw material as the optimization objective,,and the pattern layout and its sequence were integrated comprehensively to simplify the problem into combinatorial optimization of three key variables.A two-layer nesting algorithm connecting by a pre-layout pool was designed based on strong constraints in the model.The genetic algorithm of the upper layer was used to decide the sequence of orders putting into the layout pool,and a two-stage exact algorithm of the lower layer based on a"strip truncation heuristic"was designed to decide patterns.The experimental results show that the proposed algorithm can effectively reduce the low-quality solution space and has high optimization ability and solution stability.