The task assignment problem of multiple heterogeneous unmanned aerial vehicles （UAVs）, concerned with cooperative decision making and control, is studied in this paper. The heterogeneous vehicles have different oper...The task assignment problem of multiple heterogeneous unmanned aerial vehicles （UAVs）, concerned with cooperative decision making and control, is studied in this paper. The heterogeneous vehicles have different operational capabilities and kinematic constraints, and carry limited resources （e.g., weapons） onboard. They are designated to perform multiple consecutive tasks cooperatively on multiple ground targets. The problem becomes much more complicated because of these terms of heterogeneity. In order to tackle the challenge, we modify the former genetic algorithm with multi-type genes to stochastically search a best solution. Genes of chromo- somes are different, and they are assorted into several types according to the tasks that must be performed on targets. Different types of genes are processed specifically in the improved genetic operators including initialization, crossover, and mutation. We also present a mirror representation of vehicles to deal with the limited resource constraint. Feasible chromosomes that vehicles could perform tasks using their limited resources under the assignment are created and evolved by genetic operators. The effect of the proposed algorithm is demonstrated in numerical simulations. The results show that it effectively provides good feasible solutions and finds an optimal one.展开更多
【目的】提高传统的单一类别煤矸分选机器人在面对形状、尺寸差异较大的矸石时的适应性,分析异构机器人工作特性,实现异构机器人协同分选。【方法】基于深度Q值网络(deep Q network,DQN)提出异构机器人协同分选模型;分析协同工作分选流...【目的】提高传统的单一类别煤矸分选机器人在面对形状、尺寸差异较大的矸石时的适应性,分析异构机器人工作特性,实现异构机器人协同分选。【方法】基于深度Q值网络(deep Q network,DQN)提出异构机器人协同分选模型;分析协同工作分选流程制定决策框架,根据强化学习所需,设计交互环境,构建智能体连续的状态空间奖惩函数,长短期记忆网络(long short term memory,LTSM)和全连接网络相结合,构建DQN价值和目标网络,实现强化学习模型在工作过程中的任务分配。【结果】协同分选模型与传统顺序分配模型相比,在不同含矸率工作负载下,可提高分选效益0.49%~17.74%;在样本含矸率为21.61%,传送带速度为0.4~0.6 m/s的条件下,可提高分选效率2.41%~8.98%。【结论】异构机器人协同分选方法可以在不同的工作负载下获得稳定的分拣效益,避免单一分配方案无法适应动态变化的矸石流缺陷。展开更多
This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem(DHPFSP)with minimizing makespan and total energy consumption(TEC).To solve this NP-hard problem,this work proposed a com...This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem(DHPFSP)with minimizing makespan and total energy consumption(TEC).To solve this NP-hard problem,this work proposed a competitive and cooperative-based strength Pareto evolutionary algorithm(CCSPEA)which contains the following features:1)An initialization based on three heuristic rules is developed to generate a population with great diversity and convergence.2)A comprehensive metric combining convergence and diversity metrics is used to better represent the heuristic information of a solution.3)A competitive selection is designed which divides the population into a winner and a loser swarms based on the comprehensive metric.4)A cooperative evolutionary schema is proposed for winner and loser swarms to accelerate the convergence of global search.5)Five local search strategies based on problem knowledge are designed to improve convergence.6)Aproblem-based energy-saving strategy is presented to reduce TEC.Finally,to evaluate the performance of CCSPEA,it is compared to four state-of-art and run on 22 instances based on the Taillard benchmark.The numerical experiment results demonstrate that 1)the proposed comprehensive metric can efficiently represent the heuristic information of each solution to help the later step divide the population.2)The global search based on the competitive and cooperative schema can accelerate loser solutions convergence and further improve the winner’s exploration.3)The problembased initialization,local search,and energy-saving strategies can efficiently reduce the makespan and TEC.4)The proposed CCSPEA is superior to the state-of-art for solving DHPFSP.展开更多
Nowadays, hybrid satellite-terrestrial cooperative network has emerged as a key technology to provide a great variety of communication services. The deployment of this network will improve coverage and capacity in rem...Nowadays, hybrid satellite-terrestrial cooperative network has emerged as a key technology to provide a great variety of communication services. The deployment of this network will improve coverage and capacity in remote areas. Despite the benefits of this network, by increasing the number of users, communication efficiency based on interference management is a major challenge in satellite-based system. Also, the direct links between satellite system and the terrestrial equipment do not always have desirable channel condition. In order to avoid serious throughput degradation, choosing a cooperative relay node is very important. In this paper, Stackelberg game is exploited for interference management that is raised by satellites in down link over terrestrial equipment. Then, for interference management between ground station and relay node with other mobile users, CVX is used to allocate optimum power. Also, the best relay node in this structure is selected based on the harmonic mean function. Thus, the performance of the heterogeneous satellite-cooperative network is investigated based on three benchmarks, namely, successful transmission, energy consumption and outage probability. Finally, the simulation results showed the effect of proposed system model on the performance of next generation satellite networks.展开更多
Energy efficiency(EE) is a key requirement for the design of short-range communication network.In order to alleviate energy consumption(EC) constraint,a novel layered heterogeneous mobile cloud architecture is propose...Energy efficiency(EE) is a key requirement for the design of short-range communication network.In order to alleviate energy consumption(EC) constraint,a novel layered heterogeneous mobile cloud architecture is proposed in this paper.Based on the proposed layered heterogeneous mobile cloud architecture,we establish an appropriate energy consumption model,and design an energy efficiency scheme based on joint data packet fragmentation and cooperative transmission and analyze the energy efficiency corresponding to different packet sizes and the cloud size.Simulation results show that,when all nodes of the cloud are accessing the same size of data packet fragmentation,the proposed layered heterogeneous mobile cloud architecture can provide significant energy savings.The results provide useful insights into the possible operation of the strategies and show that significant energy consumption reductions are possible.展开更多
文摘The task assignment problem of multiple heterogeneous unmanned aerial vehicles （UAVs）, concerned with cooperative decision making and control, is studied in this paper. The heterogeneous vehicles have different operational capabilities and kinematic constraints, and carry limited resources （e.g., weapons） onboard. They are designated to perform multiple consecutive tasks cooperatively on multiple ground targets. The problem becomes much more complicated because of these terms of heterogeneity. In order to tackle the challenge, we modify the former genetic algorithm with multi-type genes to stochastically search a best solution. Genes of chromo- somes are different, and they are assorted into several types according to the tasks that must be performed on targets. Different types of genes are processed specifically in the improved genetic operators including initialization, crossover, and mutation. We also present a mirror representation of vehicles to deal with the limited resource constraint. Feasible chromosomes that vehicles could perform tasks using their limited resources under the assignment are created and evolved by genetic operators. The effect of the proposed algorithm is demonstrated in numerical simulations. The results show that it effectively provides good feasible solutions and finds an optimal one.
文摘【目的】提高传统的单一类别煤矸分选机器人在面对形状、尺寸差异较大的矸石时的适应性,分析异构机器人工作特性,实现异构机器人协同分选。【方法】基于深度Q值网络(deep Q network,DQN)提出异构机器人协同分选模型;分析协同工作分选流程制定决策框架,根据强化学习所需,设计交互环境,构建智能体连续的状态空间奖惩函数,长短期记忆网络(long short term memory,LTSM)和全连接网络相结合,构建DQN价值和目标网络,实现强化学习模型在工作过程中的任务分配。【结果】协同分选模型与传统顺序分配模型相比,在不同含矸率工作负载下,可提高分选效益0.49%~17.74%;在样本含矸率为21.61%,传送带速度为0.4~0.6 m/s的条件下,可提高分选效率2.41%~8.98%。【结论】异构机器人协同分选方法可以在不同的工作负载下获得稳定的分拣效益,避免单一分配方案无法适应动态变化的矸石流缺陷。
基金supported by the National Natural Science Foundation of China under Grant Nos.62076225 and 62122093the Open Project of Xiangjiang Laboratory under Grant No 22XJ02003.
文摘This work aims to resolve the distributed heterogeneous permutation flow shop scheduling problem(DHPFSP)with minimizing makespan and total energy consumption(TEC).To solve this NP-hard problem,this work proposed a competitive and cooperative-based strength Pareto evolutionary algorithm(CCSPEA)which contains the following features:1)An initialization based on three heuristic rules is developed to generate a population with great diversity and convergence.2)A comprehensive metric combining convergence and diversity metrics is used to better represent the heuristic information of a solution.3)A competitive selection is designed which divides the population into a winner and a loser swarms based on the comprehensive metric.4)A cooperative evolutionary schema is proposed for winner and loser swarms to accelerate the convergence of global search.5)Five local search strategies based on problem knowledge are designed to improve convergence.6)Aproblem-based energy-saving strategy is presented to reduce TEC.Finally,to evaluate the performance of CCSPEA,it is compared to four state-of-art and run on 22 instances based on the Taillard benchmark.The numerical experiment results demonstrate that 1)the proposed comprehensive metric can efficiently represent the heuristic information of each solution to help the later step divide the population.2)The global search based on the competitive and cooperative schema can accelerate loser solutions convergence and further improve the winner’s exploration.3)The problembased initialization,local search,and energy-saving strategies can efficiently reduce the makespan and TEC.4)The proposed CCSPEA is superior to the state-of-art for solving DHPFSP.
文摘Nowadays, hybrid satellite-terrestrial cooperative network has emerged as a key technology to provide a great variety of communication services. The deployment of this network will improve coverage and capacity in remote areas. Despite the benefits of this network, by increasing the number of users, communication efficiency based on interference management is a major challenge in satellite-based system. Also, the direct links between satellite system and the terrestrial equipment do not always have desirable channel condition. In order to avoid serious throughput degradation, choosing a cooperative relay node is very important. In this paper, Stackelberg game is exploited for interference management that is raised by satellites in down link over terrestrial equipment. Then, for interference management between ground station and relay node with other mobile users, CVX is used to allocate optimum power. Also, the best relay node in this structure is selected based on the harmonic mean function. Thus, the performance of the heterogeneous satellite-cooperative network is investigated based on three benchmarks, namely, successful transmission, energy consumption and outage probability. Finally, the simulation results showed the effect of proposed system model on the performance of next generation satellite networks.
基金jointly supported by the Chongqing Municipal Natural Science Foundation under Grant No.CSTC2013jjB40001)the National High Technology Research and Development Program of China(863Program)under Grant No.20140908the Program for Changjiang Scholars and Innovative Research Team in University under Grant No.IRT1299
文摘Energy efficiency(EE) is a key requirement for the design of short-range communication network.In order to alleviate energy consumption(EC) constraint,a novel layered heterogeneous mobile cloud architecture is proposed in this paper.Based on the proposed layered heterogeneous mobile cloud architecture,we establish an appropriate energy consumption model,and design an energy efficiency scheme based on joint data packet fragmentation and cooperative transmission and analyze the energy efficiency corresponding to different packet sizes and the cloud size.Simulation results show that,when all nodes of the cloud are accessing the same size of data packet fragmentation,the proposed layered heterogeneous mobile cloud architecture can provide significant energy savings.The results provide useful insights into the possible operation of the strategies and show that significant energy consumption reductions are possible.
