摘要
针对单一规格的一维下料问题,提出一种新的随机启发式搜索算法,在求出所有可能切割方式的情况下,搜索出最优解,而且保证最后一根原材料余料长度最长,方便以后下料。对于多规格原材料情况的一维下料分解为多个单一原材料的一维下料问题来进行求解。计算表明,与启发式算法或者遗传算法相比较,随机启发式搜索算法结构简明,易于编程,计算速度快,节材效果优。
This paper puts forward a kind of new random heuristic search algorithm for the one-dimensional cutting stock,which is used to find out all feasible cutting pattems,search the optimal solution and make sure that the final piece of raw material is the longest excess one,which is easy of the later cutting.And one-dimensional multiple size cutting stock can be divided into several single size cutting stocks.Compared to heuristic and genetic algorithms,the random heuristic search algorithm has the advantage of the simple structure,fast computing speed and high usage of material.
出处
《机械制造与自动化》
2014年第1期52-55,共4页
Machine Building & Automation
关键词
一维下料问题
优化
启发式算法
随机搜索
one-dimensional cutting stock
optimization
heuristic algorithm
random search
