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作 者:张长勇 翟一鸣 Zhang Changyong;Zhai Yiming(College of Electronic Information and Automation,Civil Aviation University of China,Tianjin 300300,China)
机构地区:[1]中国民航大学电子信息与自动化学院,天津300300
出 处:《计算机应用与软件》2022年第11期238-244,共7页Computer Applications and Software
基 金:国家自然科学基金青年科学基金项目(51707195);中央高校基本科研业务费专项基金A类项目(3122016A009)。
摘 要:以航空货运背景下不规则集装箱的货物装载问题为研究对象,搭建含有装载顺序、体积、质量、重心、不重叠等多种实际约束的航空货物堆码数学模型,采用可放置点构建、规则设定、排序、参考线引入策略,提出一种拟人算法。在此基础上,结合改进的遗传算法,实现初始装载布局方案的优化。采用多组真实航空货物数据进行实验,验证了混合遗传算法能够有效处理不规则集装箱的装载问题,可以减少空间浪费,对强异构货物有着较好的布局效果。为方便指导实际应用中的装箱操作,设计一款装箱软件来验证算法的实用性与有效性。Taking the problem of irregular container cargo loading in the context of air cargo as the research object,a mathematical model of air cargo stacking containing various practical constraints such as loading sequence,volume,mass,center of gravity,non-overlap,etc.was built.By using the strategies of constructing placeable points,setting rules,sorting and introducing reference lines,an anthropomorphic algorithm was proposed.On this basis,combined with an improved genetic algorithm,the initial loading layout plan was optimized.The experiment was carried out with several groups of real air cargo data.It verifies that the hybrid genetic algorithm can effectively handle the loading problem of irregular containers,reduce space waste,has a better layout effect for strong heterogeneous cargo.In order to easily guide the boxing operation in practical applications,a boxing software was designed to verify the practicability and effectiveness of the algorithm.
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