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Hierarchical method of task assignment for multiple cooperating UAV teams

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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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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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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Multicriteria game approach to air-to-air combat tactical decisions for multiple UAVs

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Journal of Systems Engineering and Electronics 2023年第6期34卷 1447-1464页

作者： JIANG Ruhao LUO He MA Yingying WANG Guoqiang School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization&Intelligent Decision-making Ministry of EducationHefei 230009China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei 230009China

Air-to-air combat tactical decisions for multiple unmanned aerial vehicles(ACTDMU)are a key decision-making step in beyond visual range *** influencing factors,strong antagonism and real-time requirements need to be considered in the ACTDMU *** this paper,we propose a multicriteria game approach to *** approach consists of a multicriteria game model and a Pareto Nash equilibrium *** this model,we form the strategy profiles for the integration of air-to-air combat tactics and weapon target assignment strategies by considering the correlation between them,and we design the vector payoff functions based on predominance *** propose a algorithm of Pareto Nash equilibrium based on preference relations using threshold constraints(PNE-PRTC),and we prove that the solutions obtained by this algorithm are refinements of Pareto Nash equilibrium *** numerical experiments indicate that PNE-PRTC algorithm is considerably faster than the baseline algorithms and the performance is *** on large-scale instances,the Pareto Nash equilibrium solutions can be calculated by PNEPRTC algorithm at the second *** simulation experiments show that the multicriteria game approach is more effective than one-side decision approaches such as multiple-attribute decision-making and randomly chosen decisions.

关键词： tactical decision multicriteria game preference relation Pareto Nash equilibrium.

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A multi-UAV deployment method for border patrolling based on Stackelberg game

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Journal of Systems Engineering and Electronics 2023年第1期34卷 99-116页

作者： LEI Xing HU Xiaoxuan WANG Guoqiang LUO He School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization&Intelligent Decision-making Ministry of EducationHefei 230009China Engineering Research Center for Intelligent Decision-making&Information Systems Technologies Ministry of EducationHefei 230009China

To strengthen border patrol measures, unmanned aerial vehicles(UAVs) are gradually used in many countries to detect illegal entries on borders. However, how to efficiently deploy limited UAVs to patrol on borders of large areas remains challenging. In this paper, we first model the problem of deploying UAVs for border patrol as a Stackelberg game. Two players are considered in this game: The border patrol agency is the leader,who optimizes the patrol path of UAVs to detect the illegal immigrant. The illegal immigrant is the follower, who selects a certain area of the border to pass through at a certain time after observing the leader’s strategy. Second, a compact linear programming problem is proposed to tackle the exponential growth of the number of leader’s strategies. Third, a method is proposed to reduce the size of the strategy space of the follower. Then, we provide some theoretic results to present the effect of parameters of the model on leader’s utilities. Experimental results demonstrate the positive effect of limited starting and ending areas of UAV’s patrolling conditions and multiple patrolling altitudes on the leader ’s utility, and show that the proposed solution outperforms two conventional patrol strategies and has strong robustness.

关键词： border patrol unmanned aerial vehicle(UAV) Stackelberg game compact linear programming dominated strategy elimination

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optimization of communication topology for persistent formation in case of communication faults

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Chinese Physics B 2023年第7期32卷 610-624页

作者：王国强罗贺胡笑旋台建玮 School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization&Intelligent Decision-making Ministry of EducationHefei 230009China Engineering Research Center for Intelligent Decision-making&Information Systems Technologies Ministry of EducationHefei 230009China

To address the optimization problem of communication topology for persistent formation in the case of communication faults such as link interruption,transmitter failure,and receiver failure a two-stage model including fast reconstruction of communication topology and re-optimization of communication topology is ***,a fast reconstruction algorithm of communication topology for persistent formation(FRA-CT-PF),based on optimally rigid graph,arc addition operation,and path reversal operation,is proposed,which can quickly generate a feasible reconstructed communication topology after communication faults,thus ensuring the safety of the agents and maintaining the formation shape of persistent ***,a re-optimization algorithm of communication topology for persistent formation(ROA-CTPF),based on agent position exchange,is proposed,which can further obtain a reoptimized communication topology to minimize the formation communication cost while still maintaining the formation shape of persistent *** time complexities of these two algorithms are also ***,the effectiveness of the above algorithms is verified by numerical *** with existing algorithms,FRA-CT-PF can always obtain feasible reconstructed communication topology in much less time under all communication fault scenarios,and ROA-CT-PF can obtain a reoptimized communication topology to further reduce the formation communication cost in a shorter time.

关键词： persistent formation communication topology formation communication cost communication fault

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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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