A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV s...A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV swarm needs to detect the environment first and then attack the detected targets.The heterogeneity of UAVs,multiple types of tasks,and the dynamic nature of task environment lead to uneven load and time sequence problems.This paper proposes an improved contract net protocol (CNP) based task allocation scheme,which effectively balances the load of UAVs and improves the task efficiency.Firstly,two types of task models are established,including regional reconnaissance tasks and target attack tasks.Secondly,for regional reconnaissance tasks,an improved CNP algorithm using the uncertain contract is developed.Through uncertain contracts,the area size of the regional reconnaissance task is determined adaptively after this task assignment,which can improve reconnaissance efficiency and resource utilization.Thirdly,for target attack tasks,an improved CNP algorithm using the fuzzy integrated evaluation and the double-layer negotiation is presented to enhance collaborative attack efficiency through adjusting the assignment sequence adaptively and multi-layer allocation.Finally,the effectiveness and advantages of the improved method are verified through comparison simulations.展开更多
Unlike the traditional decentralized channel,the drop-shipping channel entails a retailer relaying consumers’orders to the manufacturer,which proceeds to stock the orders and directly ship them to the consumers.This ...Unlike the traditional decentralized channel,the drop-shipping channel entails a retailer relaying consumers’orders to the manufacturer,which proceeds to stock the orders and directly ship them to the consumers.This study explores supply chain coordination and product quality in drop-shipping and traditional channels.Specifically,we analyze the performance of both channels under wholesale price and revenue-sharing contracts.Our study yields several key findings.First,the revenue-sharing contract can coordinate both traditional and drop-shipping channels,effectively increasing supply chain performance.Second,given the channel structure,the retailer prefers the wholesale price contract,whereas the manufacturer prefers the revenue-sharing contract.Third,product quality is higher in the drop-shipping channel when demand uncertainty is high.Finally,the implementation of the revenue-sharing contract increases product quality in the traditional channel,whereas it keeps product quality unchanged in the drop-shipping channel.展开更多
Cloud computing represents a novel computing model in the contemporary technology world. In a cloud system, the com- puting power of virtual machines （VMs） and network status can greatly affect the completion time o...Cloud computing represents a novel computing model in the contemporary technology world. In a cloud system, the com- puting power of virtual machines （VMs） and network status can greatly affect the completion time of data intensive tasks. How- ever, most of the current resource allocation policies focus only on network conditions and physical hosts. And the computing power of VMs is largely ignored. This paper proposes a comprehensive resource allocation policy which consists of a data intensive task scheduling algorithm that takes account of computing power of VMs and a VM allocation policy that considers bandwidth between storage nodes and hosts. The VM allocation policy includes VM placement and VM migration algorithms. Related simulations show that the proposed algorithms can greatly reduce the task comple- tion time and keep good load balance of physical hosts at the same time.展开更多
Resource allocation for an equipment development task is a complex process owing to the inherent characteristics,such as large amounts of input resources,numerous sub-tasks,complex network structures,and high degrees ...Resource allocation for an equipment development task is a complex process owing to the inherent characteristics,such as large amounts of input resources,numerous sub-tasks,complex network structures,and high degrees of uncertainty.This paper presents an investigation into the influence of resource allocation on the duration and cost of sub-tasks.Mathematical models are constructed for the relationships of the resource allocation quantity with the duration and cost of the sub-tasks.By considering the uncertainties,such as fluctuations in the sub-task duration and cost,rework iterations,and random overlaps,the tasks are simulated for various resource allocation schemes.The shortest duration and the minimum cost of the development task are first formulated as the objective function.Based on a multi-objective particle swarm optimization(MOPSO)algorithm,a multi-objective evolutionary algorithm is constructed to optimize the resource allocation scheme for the development task.Finally,an uninhabited aerial vehicle(UAV)is considered as an example of a development task to test the algorithm,and the optimization results of this method are compared with those based on non-dominated sorting genetic algorithm-II(NSGA-II),non-dominated sorting differential evolution(NSDE)and strength pareto evolutionary algorithm-II(SPEA-II).The proposed method is verified for its scientific approach and effectiveness.The case study shows that the optimization of the resource allocation can greatly aid in shortening the duration of the development task and reducing its cost effectively.展开更多
Resource allocation （RA） is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such a.s maximizing the profits, minimizing the costs, or achieving the b...Resource allocation （RA） is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such a.s maximizing the profits, minimizing the costs, or achieving the best qualities. A complex multiobjective RA is addressed, and a multiobjective mathematical model is used to find solutions efficiently. Then, all improved particie swarm algorithm （mO_PSO） is proposed combined with a new particle diversity controller policies and dissipation operation. Meanwhile, a modified Pareto methods used in PSO to deal with multiobjectives optimization is presented. The effectiveness of the provided algorithm is validated by its application to some illustrative example dealing with multiobjective RA problems and with the comparative experiment with other algorithm.展开更多
Recently the integrated modular avionics （IMA） architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture. A novel hierarchical app...Recently the integrated modular avionics （IMA） architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture. A novel hierarchical approach is proposed to solve the resource allocation problem for IMA systems in distributed environments. Firstly, the worst case response time of tasks with arbitrary deadlines is analyzed for the two-level scheduler. Then, the hierarchical resource allocation approach is presented in two levels. At the platform level, a task assignment algorithm based on genetic simulated annealing （GSA） is proposed to assign a set of pre-defined tasks to different processing nodes in the form of task groups, so that resources can be allocated as partitions and mapped to task groups. While yielding to all the resource con- straints, the algorithm tries to find an optimal task assignment with minimized communication costs and balanced work load. At the node level, partition parameters are optimized, so that the computational resource can be allocated further. An example is shown to illustrate the hierarchal resource allocation approach and manifest the validity. Simulation results comparing the performance of the proposed GSA with that of traditional genetic algorithms are presented in the context of task assignment in IMA systems.展开更多
A non-cooperative game is proposed to perform the sub-carrier assignment and power allocation for the multi-cell orthogonal frequency division multiple access（OFDMA） system.The objective is to raise the spectral eff...A non-cooperative game is proposed to perform the sub-carrier assignment and power allocation for the multi-cell orthogonal frequency division multiple access（OFDMA） system.The objective is to raise the spectral efficiency of the system and prolong the life time of user nodes.This paper defines a game player as a cell formed by the unique base station and the served users.The utility function considered here measures the user＇s achieved utility per power.Each individual cell＇s goal is to maximize the total utility of its users.To search the Nash equilibrium（NE） of the game,an iterative and distributed algorithm is presented.Since the NE is inefficient,the pricing of user＇s transmission power is introduced to improve the NE in the Pareto sense.Simulation results show the proposed game outperforms the water-filling algorithm in terms of fairness and energy efficiency.Moreover,through employing a liner pricing function,the energy efficiency could be further improved.展开更多
The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper coo...The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.展开更多
There are always large-scale items in the maintenances schedule of aircraft system, many of which have been fixed to be done in predefined sequences, which leads the workflow to be sys-tematically complex and makes th...There are always large-scale items in the maintenances schedule of aircraft system, many of which have been fixed to be done in predefined sequences, which leads the workflow to be sys-tematically complex and makes this kind of problem quite different from all sorts of existing job-selection modes. On the other hand, the human resources are always limited and men have different working capabilities on different items, which make the allocation operation of human resources be much roomy. However, the final total time span of maintenance is often required to be as short as possible in many practices, in order to suffer only the lowest cost of loss while the system is stopping. A new model for op-timizing the allocation if aircraft maintenance human resources with the constraint of predefined sequence is presented. The ge-netic algorithm is employed to find the optimal solution that holds the shortest total time span of maintenance. To generate the ul-timate maintenance work items and the human resource array, the sequences among all maintenance work items are considered firstly, the work item array is then generated through traversal with the constraint of maintenance sequence matrix, and the human resources are finally allocated according to the work item array with the constraint of the maintenance capability. An example is demonstrated to show that the model and algorithm behave a satisfying performance on finding the optimal solution as expected.展开更多
The symbol-error-rate（SER） and power allocation for hybrid cooperative（HC） transmission system are investigated.Closed-form SER expression is derived by using the moment generating function（MGF）-based approach.H...The symbol-error-rate（SER） and power allocation for hybrid cooperative（HC） transmission system are investigated.Closed-form SER expression is derived by using the moment generating function（MGF）-based approach.However,the resultant SER contains an MGF of the harmonic mean of two independent random variables（RVs）,which is not tractable in SER analysis.We present a simple MGF expression of the harmonic mean of two independent RVs which avoids the hypergeometric functions used commonly in previous studies.Using the simple MGF,closed-form SER for HC system with M-ary phase shift keying（M-PSK） signals is provided.Further,an approximation as well as an upper bound of the SER is presented.It is shown that the SER approximation is asymptotically tight.Based on the tight SER approximation,the power allocation of the HC system is investigated.It is shown that the optimal power allocation does not depend on the fading parameters of the source-destination（SD） channel and it only depends on the source-relay（SR） and relay-destination（RD） channels.Moreover,the performance gain of the power allocation depends on the ratio of the channel quality between RD and SR.With the increase of this ratio,more performance gain can be acquired.展开更多
Bicycle-sharing system is considered as a green option to provide a better connection between scenic spots and nearby metro/bus stations. Allocating and optimizing the layout of bicycle-sharing system inside the sceni...Bicycle-sharing system is considered as a green option to provide a better connection between scenic spots and nearby metro/bus stations. Allocating and optimizing the layout of bicycle-sharing system inside the scenic spot and around its influencing area are focused on. It is found that the terrain, land use, nearby transport network and scenery point distribution have significant impact on the allocation of bicycle-sharing system. While the candidate bicycle-sharing stations installed at the inner scenic points, entrances/exits and metro stations are fixed, the ones installed at bus-stations and other passenger concentration buildings are adjustable. Aiming at minimizing the total cycling distance and overlapping rate, an optimization model is proposed and solved based on the idea of cluster concept and greedy heuristic. A revealed preference/stated preference （RP/SP） combined survey was conducted at Xuanwu Lake in Nanjing, China, to get an insight into the touring trip characteristics and bicycle-sharing tendency. The results reveal that 39.81% visitors accept a cycling distance of 1-3 km and 62.50% respondents think that the bicycle-sharing system should charge an appropriate fee. The sttrvey indicates that there is high possibility to carry out a bicycle-sharing system at Xuanwu Lake. Optimizing the allocation problem cluster by cluster rather than using an exhaustive search method significantly reduces the computing amount from O（2^43） to O（43 2）. The 500 m-radius-coverage rate for the alternative optimized by 500 m-radius-cluster and 800 m-radius-cluster is 89.2% and 68.5%, respectively. The final layout scheme will provide decision makers engineering guidelines and theoretical support.展开更多
This paper generalizes the classic resource allocation problem to the resource planning and allocation problem, in which the resource itself is a decision variable and the cost of each activity is uncertain when the r...This paper generalizes the classic resource allocation problem to the resource planning and allocation problem, in which the resource itself is a decision variable and the cost of each activity is uncertain when the resource is determined. The authors formulate this problem as a two-stage stochastic programming. The authors first propose an efficient algorithm for the case with finite states. Then, a sudgradient method is proposed for the general case and it is shown that the simple algorithm for the unique state case can be used to compute the subgradient of the objective function. Numerical experiments are conducted to show the effectiveness of the model.展开更多
To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping（MQSFL） algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane...To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping（MQSFL） algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane computing and quantum computing to the shuffled frog leaping algorithm,which is an effective discrete optimization algorithm.Then the proposed MQSFL algorithm is used to solve the spectrum allocation problem of cognitive radio systems.By hybridizing the quantum frog colony optimization and membrane computing,the quantum state and observation state of the quantum frogs can be well evolved within the membrane structure.The novel spectrum allocation algorithm can search the global optimal solution within a reasonable computation time.Simulation results for three utility functions of a cognitive radio system are provided to show that the MQSFL spectrum allocation method is superior to some previous spectrum allocation algorithms based on intelligence computing.展开更多
For better reflecting the interactive defense between targets in practical combat scenarios,the basic weapon-target allocation(WTA)framework needs to be improved.A multi-stage attack WTA method is proposed.First,a def...For better reflecting the interactive defense between targets in practical combat scenarios,the basic weapon-target allocation(WTA)framework needs to be improved.A multi-stage attack WTA method is proposed.First,a defense area analysis is presented according to the targets’positions and the radii of the defense areas to analyze the interactive coverage and protection between targets’defense areas.Second,with the coverage status and coverage layer number,a multi-stage attack planning method is proposed and the multi-stage attack objective function model is established.Simulation is conducted with interactive defense combat scenarios,the traditional WTA method and the multi-stage WTA method are compared,and the objective function model is validated with the Monte-Carlo method.The results suggest that if the combat scenario involves interactive coverage of targets’defense areas,it is imperative to analyze the defense areas and apply the multi-stage attack method to weakening the target defense progressively for better combat effectiveness.展开更多
An efficient spaee-time-frequency （STF） coding strategy for multi-input multi-output orthogonal frequency division multiplexing （MIMO-OFDM） systems is presented for high bit rate data transmission over frequency s...An efficient spaee-time-frequency （STF） coding strategy for multi-input multi-output orthogonal frequency division multiplexing （MIMO-OFDM） systems is presented for high bit rate data transmission over frequency selective fading channels. The proposed scheme is a new approach to space-time-frequency coded OFDM （ODFDM） that combines OFDM with space-time coding, linear precoding and adaptive power allocation to provide higher quality of transmission in terms of the bit error rate performance and power efficiency. In addition to exploiting the maximux diversity gain in frequency, time and space, the proposed scheme enjoys high coding advantages and low-complexity decoding. The significant performance improvement of our design is confirned by corroborating numerical simulations.展开更多
In order to solve reliability-redundancy allocation problems more effectively, a new hybrid algorithm named CDEPSO is proposed in this work, which combines particle swarm optimization （PSO） with differential evoluti...In order to solve reliability-redundancy allocation problems more effectively, a new hybrid algorithm named CDEPSO is proposed in this work, which combines particle swarm optimization （PSO） with differential evolution （DE） and a new chaotic local search. In the CDEPSO algorithm, DE provides its best solution to PSO if the best solution obtained by DE is better than that by PSO, while the best solution in the PSO is performed by chaotic local search. To investigate the performance of CDEPSO, four typical reliability-redundancy allocation problems were solved and the results indicate that the convergence speed and robustness of CDEPSO is better than those of PSO and CPSO （a hybrid algorithm which only combines PSO with chaotic local search）. And, compared with the other six improved meta-heuristics, CDEPSO also exhibits more robust performance. In addition, a new performance was proposed to more fairly compare CDEPSO with the same six improved recta-heuristics, and CDEPSO algorithm is the best in solving these problems.展开更多
To minimize the overall transmit power while maintaining a constant data rate and target BER, a downlink adaptive resource allocation algorithm with jointing the exclusive manner and the shared manner is proposed for ...To minimize the overall transmit power while maintaining a constant data rate and target BER, a downlink adaptive resource allocation algorithm with jointing the exclusive manner and the shared manner is proposed for multiuser MIMO-OFDM system in correlated channels. The algorithm allocates all the subcarriers to different users according to their spatial correlations. The users with high spatial correlation are allocated in the same group and the exclusive manner is applied. The shared manner with an improved null broadening method, which improves the performance of co-channel interference （CCI） suppression and decreases the number of transmit antennas required, is applied between the different group users. As the user＇s direction of departure （DOD） changes very slowly, a looking up table method is used to reduce the computational complexity. The simulation results show that despite the angle spread of DOD, when compared with the exclusive manner, the proposed algorithm improves the spectral efficiency, and when compared with the TDMA-ZF （zero forcing） shared manner, the proposed algorithm decreases the total transmit power by at least 1 dB.展开更多
The control allocation problem of aircraft whose control inputs contain integer constraints is investigated. The control allocation problem is described as an integer programming problem and solved by the cuckoo searc...The control allocation problem of aircraft whose control inputs contain integer constraints is investigated. The control allocation problem is described as an integer programming problem and solved by the cuckoo search algorithm. In order to enhance the search capability of the cuckoo search algorithm, the adaptive detection probability and amplification factor are designed. Finally, the control allocation method based on the proposed improved cuckoo search algorithm is applied to the tracking control problem of the innovative control effector aircraft. The comparative simulation results demonstrate the superiority and effectiveness of the proposed improved cuckoo search algorithm in control allocation of aircraft.展开更多
To improve and optimize the bandwidth utilization for multi-service packet transporting system, a kind of Dynamic Full Bandwidth Utilized （DFBU） allocation algorithm allowing a single link to use far beyond its fair...To improve and optimize the bandwidth utilization for multi-service packet transporting system, a kind of Dynamic Full Bandwidth Utilized （DFBU） allocation algorithm allowing a single link to use far beyond its fair share bandwidth is presented. Three important parameters as the bound on max and minimum bandwidth, the maximum packet delay and the minimum bandwidth utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system use all the spare bandwidth （up to full-bandwidth） while the performance of fairness and QoS requirement is still guaranteed.展开更多
To improve the error performance and the resource utilization of cooperative systems, the optimum resource allocation, i.e., power allocation and partner choice, for an adaptive decode-and-forward （DF） cooperative d...To improve the error performance and the resource utilization of cooperative systems, the optimum resource allocation, i.e., power allocation and partner choice, for an adaptive decode-and-forward （DF） cooperative diversity system based on quadrature modulation is investigated. The closed-form expression of the bit error rate （BER） system performance is derived and an optimal power allocation （OPA） algorithm is proposed to optimize the power allocation between the local and relayed signals under the minimum BER criterion. Based on the OPA algorithm, a partner choice strategy is proposed to determine the partner locations specified by various cooperation gains. Simulation results show that the proposed resource optimization algorithms are superior to the unoptimized algorithms by significantly reducing the BER and improving the cooperative gain, which is useful to simplify the practical partner choice process.展开更多
基金National Natural Science Foundation of China (12202293)Sichuan Science and Technology Program (2023NSFSC0393,2022NSFSC1952)。
文摘A task allocation problem for the heterogeneous unmanned aerial vehicle (UAV) swarm in unknown environments is studied in this paper.Considering that the actual mission environment information may be unknown,the UAV swarm needs to detect the environment first and then attack the detected targets.The heterogeneity of UAVs,multiple types of tasks,and the dynamic nature of task environment lead to uneven load and time sequence problems.This paper proposes an improved contract net protocol (CNP) based task allocation scheme,which effectively balances the load of UAVs and improves the task efficiency.Firstly,two types of task models are established,including regional reconnaissance tasks and target attack tasks.Secondly,for regional reconnaissance tasks,an improved CNP algorithm using the uncertain contract is developed.Through uncertain contracts,the area size of the regional reconnaissance task is determined adaptively after this task assignment,which can improve reconnaissance efficiency and resource utilization.Thirdly,for target attack tasks,an improved CNP algorithm using the fuzzy integrated evaluation and the double-layer negotiation is presented to enhance collaborative attack efficiency through adjusting the assignment sequence adaptively and multi-layer allocation.Finally,the effectiveness and advantages of the improved method are verified through comparison simulations.
基金supported by the Key Fund Project for Youth Innovation of USTC(WK2040000042).
文摘Unlike the traditional decentralized channel,the drop-shipping channel entails a retailer relaying consumers’orders to the manufacturer,which proceeds to stock the orders and directly ship them to the consumers.This study explores supply chain coordination and product quality in drop-shipping and traditional channels.Specifically,we analyze the performance of both channels under wholesale price and revenue-sharing contracts.Our study yields several key findings.First,the revenue-sharing contract can coordinate both traditional and drop-shipping channels,effectively increasing supply chain performance.Second,given the channel structure,the retailer prefers the wholesale price contract,whereas the manufacturer prefers the revenue-sharing contract.Third,product quality is higher in the drop-shipping channel when demand uncertainty is high.Finally,the implementation of the revenue-sharing contract increases product quality in the traditional channel,whereas it keeps product quality unchanged in the drop-shipping channel.
基金supported by the National Natural Science Foundation of China(6120235461272422)the Scientific and Technological Support Project(Industry)of Jiangsu Province(BE2011189)
文摘Cloud computing represents a novel computing model in the contemporary technology world. In a cloud system, the com- puting power of virtual machines （VMs） and network status can greatly affect the completion time of data intensive tasks. How- ever, most of the current resource allocation policies focus only on network conditions and physical hosts. And the computing power of VMs is largely ignored. This paper proposes a comprehensive resource allocation policy which consists of a data intensive task scheduling algorithm that takes account of computing power of VMs and a VM allocation policy that considers bandwidth between storage nodes and hosts. The VM allocation policy includes VM placement and VM migration algorithms. Related simulations show that the proposed algorithms can greatly reduce the task comple- tion time and keep good load balance of physical hosts at the same time.
基金supported by the National Natural Science Foundation of China(71690233)
文摘Resource allocation for an equipment development task is a complex process owing to the inherent characteristics,such as large amounts of input resources,numerous sub-tasks,complex network structures,and high degrees of uncertainty.This paper presents an investigation into the influence of resource allocation on the duration and cost of sub-tasks.Mathematical models are constructed for the relationships of the resource allocation quantity with the duration and cost of the sub-tasks.By considering the uncertainties,such as fluctuations in the sub-task duration and cost,rework iterations,and random overlaps,the tasks are simulated for various resource allocation schemes.The shortest duration and the minimum cost of the development task are first formulated as the objective function.Based on a multi-objective particle swarm optimization(MOPSO)algorithm,a multi-objective evolutionary algorithm is constructed to optimize the resource allocation scheme for the development task.Finally,an uninhabited aerial vehicle(UAV)is considered as an example of a development task to test the algorithm,and the optimization results of this method are compared with those based on non-dominated sorting genetic algorithm-II(NSGA-II),non-dominated sorting differential evolution(NSDE)and strength pareto evolutionary algorithm-II(SPEA-II).The proposed method is verified for its scientific approach and effectiveness.The case study shows that the optimization of the resource allocation can greatly aid in shortening the duration of the development task and reducing its cost effectively.
基金the National Natural Science Foundation of China (60573159)
文摘Resource allocation （RA） is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such a.s maximizing the profits, minimizing the costs, or achieving the best qualities. A complex multiobjective RA is addressed, and a multiobjective mathematical model is used to find solutions efficiently. Then, all improved particie swarm algorithm （mO_PSO） is proposed combined with a new particle diversity controller policies and dissipation operation. Meanwhile, a modified Pareto methods used in PSO to deal with multiobjectives optimization is presented. The effectiveness of the provided algorithm is validated by its application to some illustrative example dealing with multiobjective RA problems and with the comparative experiment with other algorithm.
基金supported by the National Natural Science Foundation of China (60879024)
文摘Recently the integrated modular avionics （IMA） architecture which introduces the concept of resource partitioning becomes popular as an alternative to the traditional federated architecture. A novel hierarchical approach is proposed to solve the resource allocation problem for IMA systems in distributed environments. Firstly, the worst case response time of tasks with arbitrary deadlines is analyzed for the two-level scheduler. Then, the hierarchical resource allocation approach is presented in two levels. At the platform level, a task assignment algorithm based on genetic simulated annealing （GSA） is proposed to assign a set of pre-defined tasks to different processing nodes in the form of task groups, so that resources can be allocated as partitions and mapped to task groups. While yielding to all the resource con- straints, the algorithm tries to find an optimal task assignment with minimized communication costs and balanced work load. At the node level, partition parameters are optimized, so that the computational resource can be allocated further. An example is shown to illustrate the hierarchal resource allocation approach and manifest the validity. Simulation results comparing the performance of the proposed GSA with that of traditional genetic algorithms are presented in the context of task assignment in IMA systems.
基金supported by the National Natural Science Foundation of China(60972059)the Fundamental Research Funds for the Central Universities of China(2010QNA27)+2 种基金China Postdoctoral Science Foundation(20100481185)the Ph.D.Programs Foundation of Ministry of Education of China(20090095120013)the Talent Introduction Program and Young Teacher Sailing Program of China University of Mining and Technology
文摘A non-cooperative game is proposed to perform the sub-carrier assignment and power allocation for the multi-cell orthogonal frequency division multiple access（OFDMA） system.The objective is to raise the spectral efficiency of the system and prolong the life time of user nodes.This paper defines a game player as a cell formed by the unique base station and the served users.The utility function considered here measures the user＇s achieved utility per power.Each individual cell＇s goal is to maximize the total utility of its users.To search the Nash equilibrium（NE） of the game,an iterative and distributed algorithm is presented.Since the NE is inefficient,the pricing of user＇s transmission power is introduced to improve the NE in the Pareto sense.Simulation results show the proposed game outperforms the water-filling algorithm in terms of fairness and energy efficiency.Moreover,through employing a liner pricing function,the energy efficiency could be further improved.
基金Project(61801495)supported by the National Natural Science Foundation of China
文摘The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.
文摘There are always large-scale items in the maintenances schedule of aircraft system, many of which have been fixed to be done in predefined sequences, which leads the workflow to be sys-tematically complex and makes this kind of problem quite different from all sorts of existing job-selection modes. On the other hand, the human resources are always limited and men have different working capabilities on different items, which make the allocation operation of human resources be much roomy. However, the final total time span of maintenance is often required to be as short as possible in many practices, in order to suffer only the lowest cost of loss while the system is stopping. A new model for op-timizing the allocation if aircraft maintenance human resources with the constraint of predefined sequence is presented. The ge-netic algorithm is employed to find the optimal solution that holds the shortest total time span of maintenance. To generate the ul-timate maintenance work items and the human resource array, the sequences among all maintenance work items are considered firstly, the work item array is then generated through traversal with the constraint of maintenance sequence matrix, and the human resources are finally allocated according to the work item array with the constraint of the maintenance capability. An example is demonstrated to show that the model and algorithm behave a satisfying performance on finding the optimal solution as expected.
基金supported by the National Basic Research Program of China (973 Program) (2010CB731803)the National Science Foundation for Innovative Research Groups of China (60921001)
文摘The symbol-error-rate（SER） and power allocation for hybrid cooperative（HC） transmission system are investigated.Closed-form SER expression is derived by using the moment generating function（MGF）-based approach.However,the resultant SER contains an MGF of the harmonic mean of two independent random variables（RVs）,which is not tractable in SER analysis.We present a simple MGF expression of the harmonic mean of two independent RVs which avoids the hypergeometric functions used commonly in previous studies.Using the simple MGF,closed-form SER for HC system with M-ary phase shift keying（M-PSK） signals is provided.Further,an approximation as well as an upper bound of the SER is presented.It is shown that the SER approximation is asymptotically tight.Based on the tight SER approximation,the power allocation of the HC system is investigated.It is shown that the optimal power allocation does not depend on the fading parameters of the source-destination（SD） channel and it only depends on the source-relay（SR） and relay-destination（RD） channels.Moreover,the performance gain of the power allocation depends on the ratio of the channel quality between RD and SR.With the increase of this ratio,more performance gain can be acquired.
基金Project(51208261)supported by the National Natural Science Foundation of ChinaProject(12YJCZH062)supported by the Ministry of Education of Humanities and Social Science of ChinaProject(30920140132033)supported by the Fundamental Research Funds for the Central Universities,China
文摘Bicycle-sharing system is considered as a green option to provide a better connection between scenic spots and nearby metro/bus stations. Allocating and optimizing the layout of bicycle-sharing system inside the scenic spot and around its influencing area are focused on. It is found that the terrain, land use, nearby transport network and scenery point distribution have significant impact on the allocation of bicycle-sharing system. While the candidate bicycle-sharing stations installed at the inner scenic points, entrances/exits and metro stations are fixed, the ones installed at bus-stations and other passenger concentration buildings are adjustable. Aiming at minimizing the total cycling distance and overlapping rate, an optimization model is proposed and solved based on the idea of cluster concept and greedy heuristic. A revealed preference/stated preference （RP/SP） combined survey was conducted at Xuanwu Lake in Nanjing, China, to get an insight into the touring trip characteristics and bicycle-sharing tendency. The results reveal that 39.81% visitors accept a cycling distance of 1-3 km and 62.50% respondents think that the bicycle-sharing system should charge an appropriate fee. The sttrvey indicates that there is high possibility to carry out a bicycle-sharing system at Xuanwu Lake. Optimizing the allocation problem cluster by cluster rather than using an exhaustive search method significantly reduces the computing amount from O（2^43） to O（43 2）. The 500 m-radius-coverage rate for the alternative optimized by 500 m-radius-cluster and 800 m-radius-cluster is 89.2% and 68.5%, respectively. The final layout scheme will provide decision makers engineering guidelines and theoretical support.
基金supported by in part by the National Natural Science Foundation of China under Grant Nos.71390334 and 71132008the MOE Project of Key Research Institute of Humanities and Social Sciences at Universities under Grant No.11JJD630004Program for New Century Excellent Talents in University under Grant No.NCET-13-0660
文摘This paper generalizes the classic resource allocation problem to the resource planning and allocation problem, in which the resource itself is a decision variable and the cost of each activity is uncertain when the resource is determined. The authors formulate this problem as a two-stage stochastic programming. The authors first propose an efficient algorithm for the case with finite states. Then, a sudgradient method is proposed for the general case and it is shown that the simple algorithm for the unique state case can be used to compute the subgradient of the objective function. Numerical experiments are conducted to show the effectiveness of the model.
基金supported by the National Natural Science Foundation of China (61102106,61102105)the Fundamental Research Funds for the Central Universities (HEUCF100801,HEUCFZ1129)
文摘To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping（MQSFL） algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane computing and quantum computing to the shuffled frog leaping algorithm,which is an effective discrete optimization algorithm.Then the proposed MQSFL algorithm is used to solve the spectrum allocation problem of cognitive radio systems.By hybridizing the quantum frog colony optimization and membrane computing,the quantum state and observation state of the quantum frogs can be well evolved within the membrane structure.The novel spectrum allocation algorithm can search the global optimal solution within a reasonable computation time.Simulation results for three utility functions of a cognitive radio system are provided to show that the MQSFL spectrum allocation method is superior to some previous spectrum allocation algorithms based on intelligence computing.
基金the National Natural Science Foundation of China(41871376,41971416,41631072).
文摘For better reflecting the interactive defense between targets in practical combat scenarios,the basic weapon-target allocation(WTA)framework needs to be improved.A multi-stage attack WTA method is proposed.First,a defense area analysis is presented according to the targets’positions and the radii of the defense areas to analyze the interactive coverage and protection between targets’defense areas.Second,with the coverage status and coverage layer number,a multi-stage attack planning method is proposed and the multi-stage attack objective function model is established.Simulation is conducted with interactive defense combat scenarios,the traditional WTA method and the multi-stage WTA method are compared,and the objective function model is validated with the Monte-Carlo method.The results suggest that if the combat scenario involves interactive coverage of targets’defense areas,it is imperative to analyze the defense areas and apply the multi-stage attack method to weakening the target defense progressively for better combat effectiveness.
基金This project was supported by the National Natural Science Foundation of China (60272079) and the"863"High Tech-nology Research and Development Programof China (2003AA123310)
文摘An efficient spaee-time-frequency （STF） coding strategy for multi-input multi-output orthogonal frequency division multiplexing （MIMO-OFDM） systems is presented for high bit rate data transmission over frequency selective fading channels. The proposed scheme is a new approach to space-time-frequency coded OFDM （ODFDM） that combines OFDM with space-time coding, linear precoding and adaptive power allocation to provide higher quality of transmission in terms of the bit error rate performance and power efficiency. In addition to exploiting the maximux diversity gain in frequency, time and space, the proposed scheme enjoys high coding advantages and low-complexity decoding. The significant performance improvement of our design is confirned by corroborating numerical simulations.
基金Project(20040533035)supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject(60874070)supported by the National Natural Science Foundation of China
文摘In order to solve reliability-redundancy allocation problems more effectively, a new hybrid algorithm named CDEPSO is proposed in this work, which combines particle swarm optimization （PSO） with differential evolution （DE） and a new chaotic local search. In the CDEPSO algorithm, DE provides its best solution to PSO if the best solution obtained by DE is better than that by PSO, while the best solution in the PSO is performed by chaotic local search. To investigate the performance of CDEPSO, four typical reliability-redundancy allocation problems were solved and the results indicate that the convergence speed and robustness of CDEPSO is better than those of PSO and CPSO （a hybrid algorithm which only combines PSO with chaotic local search）. And, compared with the other six improved meta-heuristics, CDEPSO also exhibits more robust performance. In addition, a new performance was proposed to more fairly compare CDEPSO with the same six improved recta-heuristics, and CDEPSO algorithm is the best in solving these problems.
基金the National Natural Science Foundation of China (60572039 60432040)
文摘To minimize the overall transmit power while maintaining a constant data rate and target BER, a downlink adaptive resource allocation algorithm with jointing the exclusive manner and the shared manner is proposed for multiuser MIMO-OFDM system in correlated channels. The algorithm allocates all the subcarriers to different users according to their spatial correlations. The users with high spatial correlation are allocated in the same group and the exclusive manner is applied. The shared manner with an improved null broadening method, which improves the performance of co-channel interference （CCI） suppression and decreases the number of transmit antennas required, is applied between the different group users. As the user＇s direction of departure （DOD） changes very slowly, a looking up table method is used to reduce the computational complexity. The simulation results show that despite the angle spread of DOD, when compared with the exclusive manner, the proposed algorithm improves the spectral efficiency, and when compared with the TDMA-ZF （zero forcing） shared manner, the proposed algorithm decreases the total transmit power by at least 1 dB.
基金supported by the National Natural Science Foundation of China(61273083 and 61374012)
文摘The control allocation problem of aircraft whose control inputs contain integer constraints is investigated. The control allocation problem is described as an integer programming problem and solved by the cuckoo search algorithm. In order to enhance the search capability of the cuckoo search algorithm, the adaptive detection probability and amplification factor are designed. Finally, the control allocation method based on the proposed improved cuckoo search algorithm is applied to the tracking control problem of the innovative control effector aircraft. The comparative simulation results demonstrate the superiority and effectiveness of the proposed improved cuckoo search algorithm in control allocation of aircraft.
文摘To improve and optimize the bandwidth utilization for multi-service packet transporting system, a kind of Dynamic Full Bandwidth Utilized （DFBU） allocation algorithm allowing a single link to use far beyond its fair share bandwidth is presented. Three important parameters as the bound on max and minimum bandwidth, the maximum packet delay and the minimum bandwidth utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system use all the spare bandwidth （up to full-bandwidth） while the performance of fairness and QoS requirement is still guaranteed.
基金supported by the National High Technology Research and Development Program of China (863 program) (2006AA01Z270)the National Major Specialized Project of Science and Technology(2009ZX03003-003+4 种基金 2009ZX03003-004)the Fundamental Research Funds for the Central University (K50510010017)the Program for Changjiang Scholars and Innovative Research Team in University(IRT0852)the "111" Project (B08038)the Open Research Fund of State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University (RCS2008K003)
文摘To improve the error performance and the resource utilization of cooperative systems, the optimum resource allocation, i.e., power allocation and partner choice, for an adaptive decode-and-forward （DF） cooperative diversity system based on quadrature modulation is investigated. The closed-form expression of the bit error rate （BER） system performance is derived and an optimal power allocation （OPA） algorithm is proposed to optimize the power allocation between the local and relayed signals under the minimum BER criterion. Based on the OPA algorithm, a partner choice strategy is proposed to determine the partner locations specified by various cooperation gains. Simulation results show that the proposed resource optimization algorithms are superior to the unoptimized algorithms by significantly reducing the BER and improving the cooperative gain, which is useful to simplify the practical partner choice process.
