摘要
针对一维下料优化问题,提出了一种基于启发式多级序列线性优化思想的新算法,即将下料优化问题转化为多级序列线性优化问题求解.每级求解时,在当前可行的下料方式中选择最优的一种进行下料,不断重复此操作,直到所有剩余的坯料数目均减小至零为止.原问题的最优解就是各个序列优化问题所求得的最优下料方式的总合.计算表明,与目前常用的整数线性规划或遗传算法相比较,该算法有结构简明、计算速度快、节材效果好的优点.
Imitating human intelligence, a new algorithm based on heuristic sequential linear optimization for one-dimensional cutting-stock problem is presented. The main idea of the new algorithm is to process a global optimization problem of the cutting-stock as a sequential optimization problem by multiple stages. During every sequential stage, the best cutting pattern for the current situation is researched and processed. This stage processing is repeated until all the required stocks have been generated. Numerical examples demonstrate that it is advantageous in simplifying the program and elevating computational speed, compared with the conventional methods of linear integer programming or genetic algorithm.
出处
《大连理工大学学报》
EI
CAS
CSCD
北大核心
2004年第3期407-411,共5页
Journal of Dalian University of Technology
关键词
一维下料
整数规划
遗传算法
线性优化
序列优化
one-dimensional cutting-stock
integer programming
genetic algorithm
linear optimization
