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The total number of candidate solutions of network reconfiguration equals to the sum of candidate solutions corresponding to each spanning tree.
We have developed two resource allocation algorithms FAA and PAA under these two regimes, as solutions of network utility maximization formulations.
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The method that we present in this study has been developed to aid in the analyticalstudy of solutions of networks like the reduced respiratory population model.
A modeling and solution methodology as presented here can contribute to the efficient solution of network design models under uncertainty for reverse logistics.
The solution of network reinforcement may involve large change of the network including the LV substations and lines, which is not a favored solution currently by the utilities as to its cost and inflexibility.
In this paper, we develop a modeling method, based on queuing theory, for the solution of network performance problems faced when trying to support real-time services over Internet Protocol (IP) network.
By applying the fundamental solution matrix, the Lyapunov function, and constructing fundamental function sequences based on the solution of networks, we obtain a set of sufficient criteria which ensure the existence and global exponential stability of anti-periodic solutions of system (1.3).
The second is about the convergence of the solutions of the network equations to those of the mean-field equations.
end{cases}displaystyle end{aligned} (1.3) However, so far, there have been rare reports on the existence and exponential stability of anti-periodic solutions of neural networks, especially for neural networks with leakage delays.
To do so, the potential characteristics of sub-components (solution domain of network design) are divided into a set of partitions and then HFC-APSO is utilized to explore/exploit each of those partitions.
In this sense, the analysis of periodic solutions of neural networks could be more general than that of equilibrium points.
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