摘要
针对执行战场物资供应任务之前,不确定环境下的战场物资供应任务规划问题进行研究,并建立相应的不确定规划模型,引入一种新的启发式算法——蜂群算法,对其进行改进,构建适于解决战场物资供应任务规划问题的算法,并通过与现有算法进行性能比较,验证其有效性。最后,通过一个存在13个供应任务点的应用实例,验证提出的模型及算法的有效性。结果表明,不确定环境下得到的最佳方案更符合实际。
This paper mainly studies the battlefield material provision mission planning problem under the condition of uncertain environments, and builds up a corresponding uncertain programming model. In con- sideration of the NP-hard nature of the battlefield material provision mission planning problem, the paper introduces an elicitation algorithm, i.e. a new artificial bee colony algorithm, which is modified and is con- structed to be suitable for solving the battlefield material provision mission planning problem. And through the performance comparison of this algorithm with other algorithms, the algorithm is effective. Finally, an application study of 13 mission targets is presented and the model is verified. The results show that the op- timal plan under the uncertain environments is more practical.
出处
《空军工程大学学报（自然科学版）》
CSCD
北大核心
2014年第5期88-91,共4页
Journal of Air Force Engineering University(Natural Science Edition)
基金
陕西省自然科学基金资助项目(2013JM1003)
关键词
物资供应
任务规划
不确定理论
蜂群算法
Materials Provision
Mission Planning
Uncertain Theory
Artificial Bee Colony Algorithm
