The performance of network equipments, such as firewall, router, etc., is decided by the efficiency of patch matching. It is difficult to adapt the speed of packet matching with packets linear forwarding by traditiona...The performance of network equipments, such as firewall, router, etc., is decided by the efficiency of patch matching. It is difficult to adapt the speed of packet matching with packets linear forwarding by traditional algorithms. The purpose of this paper is to develop a novel algorithm of packet matching based on improving differential evolutionary algorithm, which also combines with classic packets matching algorithms to improve the performance of algorithm. For the sake of objectivity, the statistics method was used to compute the fitting value. Experiments showed that this new algorithm effectively improved the performance in the speed and storage space, as compared with the traditional one. For the first time, evolutionary algorithm is used to solve the network data packet forwarding, and packets can be forwarded at the linear speed. In addition, this new algorithm is universal, so it can be adapted for many equipment.展开更多
The current Whale Optimization Algorithm(WOA)has several drawbacks,such as slow convergence,low solution accuracy and easy to fall into the local optimal solution.To overcome these drawbacks,an improved Whale Optimiza...The current Whale Optimization Algorithm(WOA)has several drawbacks,such as slow convergence,low solution accuracy and easy to fall into the local optimal solution.To overcome these drawbacks,an improved Whale Optimization Algorithm(IWOA)is proposed in this study.IWOA can enhance the global search capability by two measures.First,the crossover and mutation operations in Differential Evolutionary algorithm(DE)are combined with the whale optimization algorithm.Second,the cloud adaptive inertia weight is introduced in the position update phase of WOA to divide the population into two subgroups,so as to balance the global search ability and local development ability.ANSYS and Matlab are used to establish the structure model.To demonstrate the application of the IWOA,truss structural optimizations on 52-bar plane truss and 25-bar space truss were performed,and the results were are compared with that obtained by other optimization algorithm.It is verified that,compared with WOA,the IWOA has higher efficiency,fast convergence speed,better solution accuracy and stability.So IWOA can be used in the optimization design of large truss structures.展开更多
基金Supported by the National Natural Science Foundation of China(61070008)the Humanities and Social Science Youth Fund of the Ministry of Education(11YJC870012)+2 种基金the Youth Fund of Jiangxi Province Department of Education(GJJ11106)the Natural Science Foundation of Colleges and Universities of Anhui Province Department of Education(KJ2010B096)the Industrial Research Projects of Nanchang Scienceand Technology Bureau,Jiangxi(07110076)
文摘The performance of network equipments, such as firewall, router, etc., is decided by the efficiency of patch matching. It is difficult to adapt the speed of packet matching with packets linear forwarding by traditional algorithms. The purpose of this paper is to develop a novel algorithm of packet matching based on improving differential evolutionary algorithm, which also combines with classic packets matching algorithms to improve the performance of algorithm. For the sake of objectivity, the statistics method was used to compute the fitting value. Experiments showed that this new algorithm effectively improved the performance in the speed and storage space, as compared with the traditional one. For the first time, evolutionary algorithm is used to solve the network data packet forwarding, and packets can be forwarded at the linear speed. In addition, this new algorithm is universal, so it can be adapted for many equipment.
基金This work was supported by the National Natural Science Foundation of China(Grant No.11872157 and 11532013)the graduate innovative research project of Heilongjiang University of Science and Technology(Grant No.YJSCX2020-214HKD).
文摘The current Whale Optimization Algorithm(WOA)has several drawbacks,such as slow convergence,low solution accuracy and easy to fall into the local optimal solution.To overcome these drawbacks,an improved Whale Optimization Algorithm(IWOA)is proposed in this study.IWOA can enhance the global search capability by two measures.First,the crossover and mutation operations in Differential Evolutionary algorithm(DE)are combined with the whale optimization algorithm.Second,the cloud adaptive inertia weight is introduced in the position update phase of WOA to divide the population into two subgroups,so as to balance the global search ability and local development ability.ANSYS and Matlab are used to establish the structure model.To demonstrate the application of the IWOA,truss structural optimizations on 52-bar plane truss and 25-bar space truss were performed,and the results were are compared with that obtained by other optimization algorithm.It is verified that,compared with WOA,the IWOA has higher efficiency,fast convergence speed,better solution accuracy and stability.So IWOA can be used in the optimization design of large truss structures.
