实用下料优化问题模型建立及解法

“下料问题(cuttingstockproblem)”是把相同形状的一些原材料分割加工成若干个不同规格大小的零件的问题,此类问题在工程技术和工业生产中有着重要和广泛的应用.本文首先以材料最省为原则建立模型,采用分层基因算法模型求解出模型的解,若此结果不符合时间限制条件,则通过以客户时间需求为第一目标的分组抽样模型处理后,再借助分层基因算法给出该模型的最优解.

The Practical Optimization Models of Cutting Stock Problems and Their Solutions

The ″Cutting Stock Problem″ is a problem of dividing raw materials in the same shape into several parts in different shapes. This kind of problem has important and wide appliance in engineering and industry production. The article first established a model based on the least raw material usage, and solved the model using EPFF algorithm and layered gene algorithm. If the results mismatch the time limit, we process the problem with grouping sample optimizing model first, and then work out the optimal solution of the model using layered gene algorithm.