Optimization problems are often highly constrained and evolutionary algorithms（EAs）are effective methods to tackle this kind of problems. To further improve search efficiency and convergence rate of EAs, this paper ...Optimization problems are often highly constrained and evolutionary algorithms（EAs）are effective methods to tackle this kind of problems. To further improve search efficiency and convergence rate of EAs, this paper presents an adaptive double chain quantum genetic algorithm（ADCQGA） for solving constrained optimization problems. ADCQGA makes use of doubleindividuals to represent solutions that are classified as feasible and infeasible solutions. Fitness（or evaluation） functions are defined for both types of solutions. Based on the fitness function, three types of step evolution（SE） are defined and utilized for judging evolutionary individuals. An adaptive rotation is proposed and used to facilitate updating individuals in different solutions.To further improve the search capability and convergence rate, ADCQGA utilizes an adaptive evolution process（AEP）, adaptive mutation and replacement techniques. ADCQGA was first tested on a widely used benchmark function to illustrate the relationship between initial parameter values and the convergence rate/search capability. Then the proposed ADCQGA is successfully applied to solve other twelve benchmark functions and five well-known constrained engineering design problems. Multi-aircraft cooperative target allocation problem is a typical constrained optimization problem and requires efficient methods to tackle. Finally, ADCQGA is successfully applied to solving the target allocation problem.展开更多
Device-to-Device(D2D) communication has been proposed to facilitate cellular network with system capacity(SC) and quality of service(QoS).We consider the design of link assignment(LA),channel allocation(CA)and power c...Device-to-Device(D2D) communication has been proposed to facilitate cellular network with system capacity(SC) and quality of service(QoS).We consider the design of link assignment(LA),channel allocation(CA)and power control(PC) in D2D-aided content delivery scenario for both user fairness(UF)and system throughput(ST) under QoS requirement.Due to the complexity of the problem,we decompose it into two components:CA is formulated from graph perspective to mitigate severe co-channel interference,which turns out to be the Max K-cut problem;LA and PC are jointly optimized to utilize the gain achieved from CA for supreme performance,and specifically,genetic algorithm(GA) is adopted to optimize LA,but when deriving the fitness of each chromosome,PC optimization will be involved.Thanks to numerical results,we elucidate the efficacy of our scheme.展开更多
In the system of Computer Network Collaborative Defense(CNCD),it is difficult to evaluate the trustworthiness of defense agents which are newly added to the system,since they lack historical interaction for trust eval...In the system of Computer Network Collaborative Defense(CNCD),it is difficult to evaluate the trustworthiness of defense agents which are newly added to the system,since they lack historical interaction for trust evaluation.This will lead that the newly added agents could not get reasonable initial trustworthiness,and affect the whole process of trust evaluation.To solve this problem in CNCD,a trust type based trust bootstrapping model was introduced in this research.First,the division of trust type,trust utility and defense cost were discussed.Then the constraints of defense tasks were analyzed based on game theory.According to the constraints obtained,the trust type of defense agents was identified and the initial trustworthiness was assigned to defense agents.The simulated experiment shows that the methods proposed have lower failure rate of defense tasks and better adaptability in the respect of defense task execution.展开更多
Spectrum sensing in a wideband regime for cognitive radio network(CRN) faces considerably technical challenge due to the constraints on analog-to-digital converters(ADCs).To solve this problem,an eigenvalue-based comp...Spectrum sensing in a wideband regime for cognitive radio network(CRN) faces considerably technical challenge due to the constraints on analog-to-digital converters(ADCs).To solve this problem,an eigenvalue-based compressive wideband spectrum sensing(ECWSS) scheme using random matrix theory(RMT) was proposed in this paper.The ECWSS directly utilized the compressive measurements based on compressive sampling(CS) theory to perform wideband spectrum sensing without requiring signal recovery,which could greatly reduce computational complexity and data acquisition burden.In the ECWSS,to alleviate the communication overhead of secondary user(SU),the sensors around SU carried out compressive sampling at the sub-Nyquist rate instead of SU.Furthermore,the exact probability density function of extreme eigenvalues was used to set the threshold.Theoretical analyses and simulation results show that compared with the existing eigenvalue-based sensing schemes,the ECWSS has much lower computational complexity and cost with no significant detection performance degradation.展开更多
基金supported by the National Natural Science Foundation of China(No.61004089)supported by China Scholarship Council
文摘Optimization problems are often highly constrained and evolutionary algorithms（EAs）are effective methods to tackle this kind of problems. To further improve search efficiency and convergence rate of EAs, this paper presents an adaptive double chain quantum genetic algorithm（ADCQGA） for solving constrained optimization problems. ADCQGA makes use of doubleindividuals to represent solutions that are classified as feasible and infeasible solutions. Fitness（or evaluation） functions are defined for both types of solutions. Based on the fitness function, three types of step evolution（SE） are defined and utilized for judging evolutionary individuals. An adaptive rotation is proposed and used to facilitate updating individuals in different solutions.To further improve the search capability and convergence rate, ADCQGA utilizes an adaptive evolution process（AEP）, adaptive mutation and replacement techniques. ADCQGA was first tested on a widely used benchmark function to illustrate the relationship between initial parameter values and the convergence rate/search capability. Then the proposed ADCQGA is successfully applied to solve other twelve benchmark functions and five well-known constrained engineering design problems. Multi-aircraft cooperative target allocation problem is a typical constrained optimization problem and requires efficient methods to tackle. Finally, ADCQGA is successfully applied to solving the target allocation problem.
基金supported by the National 863 projects of China(2014AA01A706)
文摘Device-to-Device(D2D) communication has been proposed to facilitate cellular network with system capacity(SC) and quality of service(QoS).We consider the design of link assignment(LA),channel allocation(CA)and power control(PC) in D2D-aided content delivery scenario for both user fairness(UF)and system throughput(ST) under QoS requirement.Due to the complexity of the problem,we decompose it into two components:CA is formulated from graph perspective to mitigate severe co-channel interference,which turns out to be the Max K-cut problem;LA and PC are jointly optimized to utilize the gain achieved from CA for supreme performance,and specifically,genetic algorithm(GA) is adopted to optimize LA,but when deriving the fitness of each chromosome,PC optimization will be involved.Thanks to numerical results,we elucidate the efficacy of our scheme.
基金supported by the National Natural Science Foundation of China under Grant No.61170295
文摘In the system of Computer Network Collaborative Defense(CNCD),it is difficult to evaluate the trustworthiness of defense agents which are newly added to the system,since they lack historical interaction for trust evaluation.This will lead that the newly added agents could not get reasonable initial trustworthiness,and affect the whole process of trust evaluation.To solve this problem in CNCD,a trust type based trust bootstrapping model was introduced in this research.First,the division of trust type,trust utility and defense cost were discussed.Then the constraints of defense tasks were analyzed based on game theory.According to the constraints obtained,the trust type of defense agents was identified and the initial trustworthiness was assigned to defense agents.The simulated experiment shows that the methods proposed have lower failure rate of defense tasks and better adaptability in the respect of defense task execution.
基金National Natural Science Foundations of China(Nos.61201161,61271335)Postdoctoral Science Foundation of Jiangsu Province of China(No.1301002B)
文摘Spectrum sensing in a wideband regime for cognitive radio network(CRN) faces considerably technical challenge due to the constraints on analog-to-digital converters(ADCs).To solve this problem,an eigenvalue-based compressive wideband spectrum sensing(ECWSS) scheme using random matrix theory(RMT) was proposed in this paper.The ECWSS directly utilized the compressive measurements based on compressive sampling(CS) theory to perform wideband spectrum sensing without requiring signal recovery,which could greatly reduce computational complexity and data acquisition burden.In the ECWSS,to alleviate the communication overhead of secondary user(SU),the sensors around SU carried out compressive sampling at the sub-Nyquist rate instead of SU.Furthermore,the exact probability density function of extreme eigenvalues was used to set the threshold.Theoretical analyses and simulation results show that compared with the existing eigenvalue-based sensing schemes,the ECWSS has much lower computational complexity and cost with no significant detection performance degradation.
