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基于AGA和集中剩余矩形区域策略的排样方法研究
引用本文:许华杰,檀洪森,胡小明.基于AGA和集中剩余矩形区域策略的排样方法研究[J].计算机应用研究,2016,33(11).
作者姓名:许华杰  檀洪森  胡小明
作者单位:广西大学计算机与电子信息学院,广西大学计算机与电子信息学院,上海第二工业大学 计算机与信息工程学院
基金项目:广西自然科学基金项目(2014GXNSFAA118382)、广西大学博士启动基金项目(XBZ140491)、上海市教育委员会科研创新项目(14ZZ167)和国家自然科学基金项目(71463003)
摘    要:针对目前工业生产中存在的矩形件排样优化问题,采用交叉概率和变异概率自适应改变的自适应遗传算法(AGA),并在遗传算法主要环节中采用改进的、性能较优的算子对排样序列进行求解,提出一种基于集中剩余矩形区域策略的解码方法并将其运用到求解过程中,以提高排样的板材利用率。经实验结果分析,所提出的排样方法在寻优能力和求解的稳定性方面均有较明显的提高,可获得较高的板材利用率,适于在生产实践中应用。

关 键 词:自适应遗传算法  矩形件排样  最低水平线算法  剩余矩形  板材利用率
收稿时间:2015/7/29 0:00:00
修稿时间:2016/9/16 0:00:00

Research of packing method based on AGA and concentrated surplus rectangle area strategy
XU Hua-jie,TAN Hongsen and HU Xiaoming.Research of packing method based on AGA and concentrated surplus rectangle area strategy[J].Application Research of Computers,2016,33(11).
Authors:XU Hua-jie  TAN Hongsen and HU Xiaoming
Affiliation:School of Computer and Electronic Information of Guangxi University,School of Computer and Electronic Information of Guangxi University,School of Computer and Information Engineering of Shanghai Second Polytechnic University
Abstract:Focused on the rectangular packing optimization problems among the craft production of current industries, this paper applied adaptive genetic algorithm (AGA) in which the crossover probability and mutation probability could adaptively adjust and the improved operators with better performance to solve the packing problem. This paper presented a decoding method based on concentrated surplus rectangle area strategy and applied it into the solving process to improve the utilization of sheet. According to the experiment results, the optimization capacity and stability of solution are improved obviously with the proposed packing method. A higher utilization of sheet is acquired according to the proposed packing method which is fit for productive practice.
Keywords:adaptive genetic algorithm  rectangular packing  lowest horizontal line  surplus rectangle  utilization of sheet
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