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基于改进差分进化算法的动态防空资源分配优化

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系统仿真学报 2024年第6期36卷 1285-1297页

作者：罗天羽邢立宁王锐王凌石建迈孙昕国防科技大学系统工程学院湖南长沙410073 西安电子科技大学电子工程学院陕西西安710071 清华大学自动化系北京100084

面对动态防空资源分配问题中存在的空袭目标突现和雷达、发射车等资源受干扰现象,在综合考虑雷达、发射车和导弹等武器装备性能的基础上,基于目标集、资源集建立了最小化目标总拦截价值与生存概率的混合整数决策模型。提出了一种新的改... 详细信息

面对动态防空资源分配问题中存在的空袭目标突现和雷达、发射车等资源受干扰现象,在综合考虑雷达、发射车和导弹等武器装备性能的基础上,基于目标集、资源集建立了最小化目标总拦截价值与生存概率的混合整数决策模型。提出了一种新的改进差分进化算法进行求解,采用反向学习策略生成初始解,确保初始种群的质量,设计了一种快速修复与重构的启发式规则作用于多阶段,以提升算法的搜索能力。仿真实验验证了该算法具有求解时间和求解精度上的优越性。该研究能使武器系统在动态事件的随机影响下,保持高效的作战能力和决策效果。

关键词：防空作战动态防空资源分配反向学习改进差分进化算法

Weapon configuration, allocation and route planning with time windows for multiple unmanned combat air vehicles

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Journal of Systems Engineering and Electronics 2018年第5期29卷 953-968页

作者： ZHANG Jiaming LIU Zhong shi jianmai CHEN Chao Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology

Unmanned combat air vehicles(UCAVs) mission planning is a fairly complicated global optimum problem. Military attack missions often employ a fleet of UCAVs equipped with weapons to attack a set of known targets. A UCAV can carry different weapons to accomplish different combat missions. Choice of different weapons will have different effects on the final combat effectiveness. This work presents a mixed integer programming model for simultaneous weapon configuration and route planning of UCAVs, which solves the problem optimally using the IBM ILOG CPLEX optimizer for simple missions. This paper develops a heuristic algorithm to handle the medium-scale and large-scale problems. The experiments demonstrate the performance of the heuristic algorithm in solving the medium scale and large scale problems. Moreover, we give suggestions on how to select the most appropriate algorithm to solve different scale problems.

关键词： unmanned combat air vehicles(UCAVs) mission planning route planning weapon configuration time windows

COORDINATING PRODUCTION AND RECYCLING DECISIONS WITH STOCHASTIC DEMAND AND RETUR

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Journal of Systems Science and Systems Engineering 2010年第4期19卷 385-407页

作者： jianmai shi Guoqing ZHANG Jichang SHA Saman Hassanzadeh AMIN School of Information System and Management National University of Defense Technology Changsha Hunan China Department of Industrial and Manufacturing Systems Engineering University of Windsor Windsor Ontario Canada

In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints ？ the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time.

关键词： Closed loop supply chain uncertain demand uncertain return reverse logistics Lagrangian relaxation

Joint mission and route planning of unmanned air vehicles via a learning-based heuristic

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Journal of Systems Engineering and Electronics 2023年第1期34卷 81-98页

作者： shi jianmai ZHANG Jiaming LEI Hongtao LIU Zhong WANG Rui College of Systems Engineering National University of Defense TechnologyChangsha 410073China

Unmanned air vehicles(UAVs) have been regularly employed in modern wars to conduct different missions. Instead of addressing mission planning and route planning separately,this study investigates the issue of joint mission and route planning for a fleet of UAVs. The mission planning determines the configuration of weapons in UAVs and the weapons to attack targets, while the route planning determines the UAV’s visiting sequence for the targets. The problem is formulated as an integer linear programming model. Due to the inefficiency of CPLEX on large scale optimization problems, an effective learningbased heuristic, namely, population based adaptive large neighborhood search(P-ALNS), is proposed to solve the model. In P-ALNS, seven neighborhood structures are designed and adaptively utilized in terms of their historical performance. The effectiveness and superiority of the proposed model and algorithm are demonstrated on test instances of small, medium and large sizes. In particular, P-ALNS achieves comparable solutions or as good as those of CPLEX on small-size(20 targets)instances in much shorter time.

关键词： unmanned air vehicle(UAV) mission planning routing adaptive large neighborhood search

Modeling and solution based on stochastic games for development of COA under uncertainty

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Journal of Systems Engineering and Electronics 2019年第2期30卷 288-296页

作者： CHEN Chao DU Zhengjun LIANG Xingxing shi jianmai ZHANG Hao Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Unit 61683 of the PLA Naval War Gaming Center Naval Command College

Developing a course of action(COA) is a key step in military planning. In most extant studies on the COA development,only the unilateral actions of friendly forces are considered. Based on stochastic games, we propose models that could deal with the complexities and uncertainties of wars. By analyzing the equilibrium state of both opponent sides, outcomes preferable to one side could be achieved by adopting the methods obtained from the proposed models. This research could help decision makers take the right COA in a state of uncertainty.

关键词： course of action (COA) uncertainty of antagonism outcomes stochastic games

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资源不确定军事任务计划预测调度模型与算法

国防科技大学学报 2013年第3期35卷 30-35页

作者：张迎新陈超刘忠石建迈国防科技大学信息系统工程重点实验室湖南长沙410073

针对军事任务计划执行环境中普遍存在的资源不确定性,提出了基于资源缓冲区的军事任务计划预测调度算法。算法首先基于平台有效资源功能向量进行任务—平台分配,分配过程中通过调节平台有效资源功能向量,获得不同的平台资源缓冲区分配方... 详细信息

针对军事任务计划执行环境中普遍存在的资源不确定性,提出了基于资源缓冲区的军事任务计划预测调度算法。算法首先基于平台有效资源功能向量进行任务—平台分配,分配过程中通过调节平台有效资源功能向量,获得不同的平台资源缓冲区分配方案;然后基于NSGA-Ⅱ算法框架对军事任务计划进行多目标求解,进而获得问题的Pareto最优解集。文章通过仿真算例对算法的可行性和有效性进行验证,实验结果表明,该算法能够有效求解资源不确定军事任务计划问题。

关键词：军事任务计划作战行动序列预测调度资源缓冲区

考虑飞行初段弹道交叉的多导弹协同发射时序规划方法

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系统工程与电子技术 2017年第2期39卷 316-321页

作者：张家铭刘忠石建迈陈超张明星国防科学技术大学信息系统工程重点实验室湖南长沙410073

在多导弹协同作战条件下,协调不同导弹发射平台之间的导弹发射顺序,避免导弹飞行初段弹道的相互干扰,快速计算所有导弹的发射时间变得十分迫切和异常困难。为解决多导弹协同发射时序规划问题,以最小化完成导弹发射任务的最终时间为优化... 详细信息

在多导弹协同作战条件下,协调不同导弹发射平台之间的导弹发射顺序,避免导弹飞行初段弹道的相互干扰,快速计算所有导弹的发射时间变得十分迫切和异常困难。为解决多导弹协同发射时序规划问题,以最小化完成导弹发射任务的最终时间为优化目标,建立了多导弹发射时序协同规划的混合整数规划模型。设计了快速启发式算法,给出了发射时间求解算法及基于空间压缩思想的可行解进化策略,可辅助指挥员快速生成导弹发射时序方案。以30枚导弹协同发射为案例,对模型和算法进行了仿真验证。实验结果表明,该模型和方法能有效解决多导弹协同发射时序规划问题。

关键词：巡航导弹发射时序任务规划弹道交叉

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考虑航线交叉的救援直升机起飞时序规划方法

国防科技大学学报 2015年第6期37卷 103-109页

作者：张家铭刘忠石建迈贺云岳王一杉陈超国防科技大学信息系统与管理学院中国人民解放军63796部队

为解决多架救援直升机的起飞时序规划问题,以最小化最后一架救援直升机的起飞时间为优化目标,建立多直升机多起降点的数学规划模型。设计了基于任务优先级的快速启发式算法,提出航线交叉点的处理方案,给出起飞时间求解算法。以云南鲁甸... 详细信息

为解决多架救援直升机的起飞时序规划问题,以最小化最后一架救援直升机的起飞时间为优化目标,建立多直升机多起降点的数学规划模型。设计了基于任务优先级的快速启发式算法,提出航线交叉点的处理方案,给出起飞时间求解算法。以云南鲁甸6.8级地震的灾后救援为背景,设计了包含24架直升机和12个起飞点的起飞时序规划案例,对模型和算法进行了仿真验证,并对航线交叉的影响与处理措施进行了深入讨论。实验结果表明该模型和方法能有效解决多架救援直升机的起飞时序规划问题。

关键词：灾害救援救援直升机任务规划航线交叉

基于匈牙利-模拟退火算法的多阶段武器目标分配方法

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系统工程与电子技术 2023年第11期45卷 3507-3514页

作者：常雪凝石建迈陈超黄金才国防科技大学系统工程学院湖南长沙410003

针对现代化战争中远程精确制导武器成本高昂以及武器发射平台数量有限的问题,研究了多阶段武器目标分配问题,以最小化武器成本为优化目标,建立了混合整数非线性规划模型。设计了一种集成匈牙利和模拟退火的混合智能搜索算法,首先根据待... 详细信息

针对现代化战争中远程精确制导武器成本高昂以及武器发射平台数量有限的问题,研究了多阶段武器目标分配问题,以最小化武器成本为优化目标,建立了混合整数非线性规划模型。设计了一种集成匈牙利和模拟退火的混合智能搜索算法,首先根据待攻击目标的时空状态与毁伤特性确定打击阶段、标记可松弛性。在模拟退火的框架下,基于目标的松弛性调整攻击阶段,再通过匈牙利算法计算每个阶段武器和目标的精确匹配方案。通过启发式算法和精确求解技术的结合,在保证求解质量的前提下,极大减少了计算时间。通过计算实验,与变邻域搜索算法进行了对比分析,验证了该算法在求解多阶段武器目标分配问题的有效性。仿真结果表明,所提算法在计算时间和求解效果上优于变邻域搜索算法。

关键词：武器目标分配多阶段匈牙利算法模拟退火算法