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Robust decision making for UAV air-to-ground attack under severe uncertainty

Journal of Central South University 2015年第11期22卷 4263-4273页

作者：胡笑旋陈意罗贺 School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

As unmanned aerial vehicles(UAVs) are used more and more in military operations, increasing their level of autonomous decision making becomes necessary. In uncertain battlefield environments, when making sovereign decisions, UAVs must choose low-risk options. An integrated framework is proposed for UAV robust decision making in air-to-ground attack missions under severe uncertainty. In the offline part of the framework, the battlefield scenarios are analyzed and an influence diagram is built to represent the decision situation. In the online part, the UAV evaluates the alternative actions for every scenario, and then the optimal robust action is chosen, using the robust decision model. Results of simulation show that the proposed approach is feasible and effective. The framework can support UAVs in making independent robust decisions under circumstances which require immediate responses under severe uncertainty, and it can also be extended to applications in more complex situations.

关键词： unmanned aerial vehicle severe uncertainty robust

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Generation of optimal persistent formations for heterogeneous multi-agent systems with a leader constraint

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Chinese Physics B 2018年第2期27卷 645-654页

作者：王国强罗贺胡笑旋 School of Management Hefei University of Technology Key Laboratory of Process Optimization & Intelligent Decision-making Ministry of Education

In this study, we consider the generation of optimal persistent formations for heterogeneous multi-agent systems, with the leader constraint that only specific agents can act as leaders. We analyze three modes to control the optimal persistent formations in two-dimensional space, thereby establishing a model for their constrained generation. Then, we propose an algorithm for generating the optimal persistent formation for heterogeneous multi-agent systems with a leader constraint （LC-HMAS-OPFGA）, which is the exact solution algorithm of the model, and we theoretically prove its validity. This algorithm includes two kernel sub-algorithms, which are optimal persistent graph generating algorithm based on a minimum cost arborescence and the shortest path （MCA-SP-OPGGA）, and the optimal persistent graph adjusting algorithm based on the shortest path （SP-OPGAA）. Under a given agent formation shape and leader constraint, LC-HMAS-OPFGA first generates the network topology and its optimal rigid graph corresponding to this formation shape. Then, LC-HMAS- OPFGA uses MCA-SP-OPGGA to direct the optimal rigid graph to generate the optimal persistent graph. Finally, LC- HMAS-OPFGA uses SP-OPGAA to adjust the optimal persistent graph until it satisfies the leader constraint. We also demonstrate the algorithm, LC-HMAS-OPFGA, with an example and verify its effectiveness.

关键词： leader constraint heterogeneous multi-agent system optimal persistent formation minimum costarborescence

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Hierarchical method of task assignment for multiple cooperating UAV teams

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Journal of Systems Engineering and Electronics 2015年第5期26卷 1000-1009页

作者： Xiaoxuan Hu Huawei Ma Qingsong Ye He Luo School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

The problem of task assignment for multiple cooperating unmanned aerial vehicle(UAV) teams is considered. Multiple UAVs forming several small teams are needed to perform attack tasks on a set of predetermined ground targets. A hierarchical task assignment method is presented to address the problem. It breaks the original problem down to three levels of sub-problems: target clustering, cluster allocation and target assignment. The first two sub-problems are centrally solved by using clustering algorithms and integer linear programming, respectively, and the third sub-problem is solved in a distributed and parallel manner, using a mixed integer linear programming model and an improved ant colony algorithm. The proposed hierarchical method can reduce the computational complexity of the task assignment problem considerably, especially when the number of tasks or the number of UAVs is large. Experimental results show that this method is feasible and more efficient than non-hierarchical methods.

关键词： unmanned aerial vehicle(UAV) task assignment clustering integer linear programming ant colony optimization(ACO) algorithm

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Fuzziness parameter selection in fuzzy c-means: The perspective of cluster validation

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Science China(Information Sciences) 2014年第11期57卷 252-259页

作者： ZHOU KaiLe FU Chao YANG ShanLin School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education

Fuzzy c-means(FCM) algorithm is an important clustering method in pattern recognition, while the fuzziness parameter, m, in FCM algorithm is a key parameter that can significantly affect the result of clustering. Cluster validity index(CVI) is a kind of criterion function to validate the clustering results, thereby determining the optimal cluster number of a data set. From the perspective of cluster validation, we propose a novel method to select the optimal value of m in FCM, and four well-known CVIs, namely XB, VK, VT, and SC, for fuzzy clustering are used. In this method, the optimal value of m is determined when CVIs reach their minimum values. Experimental results on four synthetic data sets and four real data sets have demonstrated that the range of m is [2, 3.5] and the optimal interval is [2.5, 3].

关键词： clustering fuzziness parameter fuzzy c-means(FCM) cluster validation cluster validity index

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An Adaptive Local Grid Nesting-based Genetic Algorithm for Multi-earth Observation Satellites' Area Target Observation

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Journal of Systems Science and Systems Engineering 2024年第2期33卷 232-258页

作者： Ligang Xing Wei Xia Xiaoxuan Hu Waiming Zhu Yi Wu School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization and Inteligent Decision-making Ministry of EducationHefei 230009China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei 230009China

The Scheduling of the Multi-EOSs Area Target Observation(SMEATO)is an EOS resource schedul-ing problem highly coupled with computational *** advances in EOS technology and the ex-pansion of wide-area remote sensing applications have increased the practical significance of *** this paper,an adaptive local grid nesting-based genetic algorithm(ALGN-GA)is proposed for developing SMEATO ***,a local grid nesting(LGN)strategy is designed to discretize the target area into parts,so as to avoid the explosive growth of calculations.A genetic algorithm(GA)framework is then used to share reserve information for the population during iterative evolution,which can generate high-quality solutions with low computational *** this basis,an adaptive technique is introduced to determine whether a local region requires nesting and whether the grid scale is *** effectiveness of the proposed model is assessed experimentally with nine randomly generated tests at different *** results show that the ALGN-GA offers advantages over several conventional algorithms in 88.9%of instances,especially in large-scale *** fully demonstrate the high efficiency and stability of the ALGN-GA.

关键词： Multi-EOSs scheduling area target observation adaptive genetic algorithm local grid nesting

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A MILP Model and Two-Stage Heuristic Algorithm for Vehicle-Assisted Multi-Drone Inspection Routing Problem

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IET Intelligent Transport Systems 2025年第1期19卷

作者： Xia, Yuanqing Luo, He Dong, Rui Yin, Youlong Lin, Shizhong Wang, Guoqiang School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization & Intelligent Decision-Making Ministry of Education Hefei China Engineering Research Center for Intelligent Management of Aerospace System Anhui Province Hefei China Management Center of UAV Inspection Operation State Grid Anhui Electric Power Co. Ltd Hefei China Anhui Power Transmission & Transformation Engineering Co. Ltd Hefei China

This paper introduces a vehicle-assisted multi-drone inspection routing problem (VAMDIRP), which enables the vehicle to repeatedly traverse roads, thereby reducing task completion time. Firstly, a mixed-integer linear programming (MILP) model is constructed for the problem using a series of decision variables and auxiliary variables. The model can be solved by GUROBI for small-scale instances. Secondly, a two-stage heuristic algorithm is proposed to solve large-scale instances. Experimental results show that this algorithm improves the solution quality by an average of 20.71% and reduces the running time by an average of 60.31% compared to existing algorithms. Finally, a sensitivity analysis is conducted on relevant parameters, revealing that changes in the number and speed of drones significantly affect the solution quality. © 2025 The Author(s). IET Intelligent Transport Systems published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Sensitivity analysis

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Agile Earth Observation Satellite Scheduling Algorithm for Emergency Tasks Based on Multiple Strategies

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Journal of Systems Science and Systems Engineering 2021年第5期30卷 626-646页

作者： Haiquan Sun Wei Xia Zhilong Wang Xiaoxuan Hu aSchool of Management Hefei University of TechnologyHefeiChina Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of EducationHefeiChina

During the execution of imaging tasks,satellites are often required to observe natural disasters,local wars,and other emergencies,which regularly interferes with the execution of existing ***,rapid satellite scheduling is urgently *** a new generation of three degree-of-freedom(roll,pitch,and yaw)satellites,agile earth observation satellites(AEOSs)have longer variable-pitch visible time windows for ground targets and are capable of observing at any time within the time ***,they are very suitable for emergency ***,current task scheduling models and algorithms ignore the time,storage and energy consumed by ***,these cannot make full use of the AEOS capabilities to optimize the scheduling for emergency *** this study,we present a fine scheduling model and algorithm to realize the AEOS scheduling for emergency ***,a novel time window division method is proposed to convert a variable-pitch visible time window to multiple fixed-pitch visible time ***,a model that considers flexible pitch and roll capabilities is ***,a scheduling algorithm based on merging insertion,direct insertion,shifting insertion,deleting insertion,and reinsertion strategies is proposed to solve conflicting problems *** verify the effectiveness of the algorithm,48 groups of comparative experiments are carried *** experimental results show that the model and algorithm can improve the emergency task completion efficiency of AEOSs and reduce the disturbance measure of the ***,the proposed method can support hybrid satellite resource scheduling for emergency tasks.

关键词： Agile earth observation satellites emergency tasks merging insertion shifting insertion

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A mixture of HMM,GA,and Elman network for load prediction in cloud-oriented data centers

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Journal of Zhejiang University-Science C(Computers and Electronics) 2013年第11期14卷 845-858页

作者： Da-yu XU Shan-lin YANG Ren-ping LIU MOE Key Laboratory of Process Optimization and Intelligent Decision-Making Hefei University of Technology Information and Communication Technologies Centre CSIRO

The rapid growth of computational power demand from scientific,business,and Web applications has led to the emergence of cloud-oriented data *** centers use pay-as-you-go execution environments that scale transparently to the *** prediction is a significant cost-optimal resource allocation and energy saving approach for a cloud computing *** linear or nonlinear prediction models that forecast future load directly from historical information appear less *** classification before prediction is necessary to improve prediction *** this paper,a novel approach is proposed to forecast the future load for cloud-oriented data ***,a hidden Markov model(HMM) based data clustering method is adopted to classify the cloud *** Bayesian information criterion and Akaike information criterion are employed to automatically determine the optimal HMM model size and cluster *** HMMs are then used to identify the most appropriate cluster that possesses the maximum likelihood for current *** the data from this cluster,a genetic algorithm optimized Elman network is used to forecast future *** results show that our algorithm outperforms other approaches reported in previous works.

关键词： Cloud computing Load prediction Hidden Markov model Genetic algorithm Elman network

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Impacts of Platform’s Omnichannel Coupons on Multichannel Suppliers

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Journal of Systems Science and Systems Engineering 2023年第1期32卷 71-99页

作者： Yue Zhang Xiaojian Hu Ju Zhao Ju Qiu School of Management Hefei University of TechnologyHefei230009China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of EducationHefei230009China

While coupons that can be redeemed only in online channels have been issued by e-commerce platforms for decades, a new type of platform’s coupons, i.e., omnichannel coupons, which can be redeemed in both online and store channels, is gaining popularity with the rise of the omnichannel retail mode. It is interesting to explore the conditions under which omnichannel coupons are more advantageous to platforms and multichannel suppliers that sell products through platforms and physical stores. Two game models are developed in two cases where an e-commerce platform offers single channel coupons or omnichannel coupons for a multichannel supplier. Two scenarios are considered: one in which a consumer’s valuation of a product that fits his or her need is homogeneous and another in which the valuation is heterogeneous. Equilibrium outcomes show that under the homogeneous scenario, the product price and coupon face value in both coupon modes increase with the product’s fit probability when the cross-selling revenue is high, while decrease with the product’s fit probability when the cross-selling revenue is low. However, under the heterogeneous scenario, the price in both modes increases with the product’s fit probability only when the supplier’s loss from returns is low and the cross-selling revenue is high, and the coupon face value always decreases with the product’s fit probability. Compared with single channel coupons, omnichannel coupons may lead to a higher product price under certain conditions. Furthermore, omnichannel coupons can lead to higher total demand and benefit both the platform and the supplier if and only if the product’s fit probability is low and the supplier’s loss from returns is high. An extension shows that the platform’s preference for omnichannel coupons is weakened when the supplier offers a partial refund policy.

关键词： Omnichannel coupon promotion e-commerce platform game theory

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Optimal search for moving targets with sensing capabilities using multiple UAVs

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Journal of Systems Engineering and Electronics 2017年第3期28卷 526-535页

作者： Xiaoxuan Hu Yanhong Liu Guoqiang Wang School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of EducationHefei 230009China

This paper studies the problem of using multiple unmanned air vehicles (UAVs) to search for moving targets with sensing capabilities. When multiple UAVs (multi-UAV) search for a number of moving targets in the mission area, the targets can intermittently obtain the position information of the UAVs from sensing devices, and take appropriate actions to increase the distance between themselves and the UAVs. Aiming at this problem, an environment model is established using the search map, and the updating method of the search map is extended by considering the sensing capabilities of the moving targets. A multi-UAV search path planning optimization model based on the model predictive control (MPC) method is constructed, and a hybrid particle swarm optimization algorithm with a crossover operator is designed to solve the model. Simulation results show that the proposed method can effectively improve the cooperative search efficiency and can find more targets per unit time compared with the coverage search method and the random search method.

关键词： unmanned air vehicle (UAV) moving target search model predictive control path planning hybrid particle swarm optimization

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