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作 者:许洁林 张灏龙 李静[1] 杨仪菲 XU Jie-lin;ZHANG Hao-long;LI Jing;YANG Yi-fei(China Academy of Aerospace Systems Science and Engineering,Beijing 100037,China)
机构地区:[1]中国航天系统科学与工程研究院,北京100037
出 处:《计算机仿真》2025年第1期13-18,共6页Computer Simulation
摘 要:联合作战是未来重要作战形式。伴随联合作战指挥控制系统中装备组合优化解空间的爆炸式增长,研究如何能够快速地从可调用装备库中抽取合适的装备组合方案,即装备组合优化问题,对未来指挥控制系统的建设有重要意义。首先,分析了装备组合优化模型及其求解算法的研究现状,发现存在优化方法主观性及忽略时间这一战场装备调用重要影响因素的不足。因此,文中构建了时间最小化、成本最小化、能力最大化的装备组合优化模型。同时,提出利用装备实际使用约束缩减解空间的新思路,并基于多目标模拟退火算法,根据装备组合优化问题的特点对新解生成方法进行改进,提出了新的装备组合优化算法。最后,利用小规模数据集实验及大规模数据集实验验证了算法的寻优能力及改进有效性。Joint operations are an important form of warfare in the future.With the explosive growth of the solution space for equipment combination optimization in the joint operation command and control system,researching how to quickly extract suitable equipment combination schemes from the available equipment library,namely the equipment combination optimization problem,is of great significance for the construction of future command and control systems.This paper first analyzes the equipment combination optimization model and its solution algorithm in recent years,and finds that there are some shortcomings.The optimization method has a certain degree of subjectivity and ignores time which is an important influencing factor of battlefield equipment deployment.Therefore,an equipment combination optimization model was built to minimize time,cost and maximize capacity.At the same time,a new idea of using the constraints of actual use of equipment to reduce the solution space is proposed.Based on the multi-objective simulated annealing algorithm,the new solution generation method is improved according to the characteristics of the equipment combination optimization problem,and a new equipment combination optimization algorithm is proposed.Finally,small-scale dataset experiments and large-scale dataset experiments are used to verify the optimization ability and improvement effectiveness of the algorithm.
分 类 号:TP391.9[自动化与计算机技术—计算机应用技术]
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