基于自适应遗传模拟退火算法的矩形件排样  

Packing of rectangles using adaptive genetic simulated annealing algorithm

作　　者：夏以冲 陈秋莲[1] 宋仁坤 XIAYichong;CHEN Qiulian;SONG Renkun(School of Computer and Electronic Information,Guangxi University,Nanning 530004,China)

机构地区：[1]广西大学计算机与电子信息学院,南宁530004

出　　处：《计算机工程与应用》2018年第22期229-232,245,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.71371058;No.61363026)

摘　　要：研究一种自适应遗传模拟退火算法,应用于矩形件优化排样问题。以整数编码矩形件的排样序列,采用经验选择与随机生成相结合的策略构造初始种群。运用自适应交叉和变异概率动态地控制遗传算法的收敛速度,通过模拟退火算法引导全局最优搜索,采用启发式最低水平线择优算法对排样序列进行解码,形成排样方式。多组对比实验结果表明,自适应遗传模拟退火算法求解速度较快,可以有效提高板材的利用率。An adaptive genetic simulated annealing algorithm applied to the problem of packing optimization of rectangles is studied in this paper.The packing sequence of rectangles is coded by integer.The initial population is constructed by the combination of empirical selection and stochastic generation.And the adaptive crossover probability and mutation probability are adopted to control the convergent speed of genetic algorithm dynamically.A simulated annealing algorithm is used to lead the search scope developed in the direction of global optimal.It uses the heuristic optimization strategy of lowest horizontal line algorithm as decoding method of packing sequence and forms the cutting patterns.Multiple sets of experimental results show that the adaptive genetic simulated annealing algorithm with high solving speed can effectively increase the utilization of sheet.

关 键 词：排样优化 自适应遗传算法 模拟退火 最低水平线择优 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术]