MapReduce技术在物资调运与配载问题中的应用  

Application of MapReduce Technology in Problem of Material Transportation and Stowage

作　　者：陈元文 CHEN Yuanwen(College of Equipment Management and Support,Engineering University of Chinese People’s Armed Police Force,Xi’an 710086,China)

机构地区：[1]武警工程大学装备管理与保障学院,西安710086

出　　处：《计算机工程与应用》2021年第12期273-278,共6页Computer Engineering and Applications

基　　金：国家部委科研项目。

摘　　要：针对用于求解复杂物资调运及配载问题的多目标遗传算法耗时较长的问题,设计了基于云计算MapReduce技术的并行化部署和改进方案。实验对比了算法在多种串行、并行环境下的时效性,证实了MapReduce架构在一定环境下能较大幅度提高算法的时耗性能。Aiming at the problem that multi-objective genetic algorithms for solving complex material scheduling and stowage problems take a long time,this paper designs a parallel deployment and improvement scheme based on cloud computing MapReduce technology.The experiments compare the timeliness of the algorithm in a variety of serial and par-allel environments,confirming that the MapReduce architecture can greatly improve the time-consuming performance of the algorithm under certain circumstances.

关 键 词：物资调运及配载 多目标遗传算法 MAPREDUCE 并行化 

分 类 号：TP3-05[自动化与计算机技术—计算机科学与技术]