基于遗传算法的大规模矩形件优化排样  

A genetic algorithm for the layout of large scale rectangular parts

作　　者：马炫[1] 张亚龙[1] 

机构地区：[1]西安理工大学自动化与信息工程学院,陕西西安710048

出　　处：《智能系统学报》2007年第5期48-52,共5页CAAI Transactions on Intelligent Systems

摘　　要：大规模矩形件优化排样是一个典型的组合优化问题,属于NP-hard问题.实际工程中对一个排样方案一般有满足"一刀切"的工艺要求,"一刀切"要求增加了对排样的约束.提出的优化算法,将矩形匹配分割算法作为遗传算法染色体的解码器实现一个排样方案,用遗传算法进行排样方案的全局搜索.算例比较表明,该算法可以求得满足"一刀切"约束的最优解.The optimal layout of large scale rectangular parts is a combinatorial optimization problem, a typical NP-hard one. In practical engineering, quire cutting is often requested, which increases the constraints in the determination of a layout. To satisfy quire cutting requirements, in this paper, an optimization algorithm is proposed wherein a rectangular matching and segmentation algorithm is employed as a decoder of chromosomes in a genetic algorithm to determine placement. A global optimal solution for placement can be achieved with this genetic algorithm. Simulation results confirmed the validity of the proposed algorithm.

关 键 词：遗传算法 矩形件排样 组合优化 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]