Sentence examples for formulated resource from inspiring English sources

As a result, we are able to show that the Nash equilibrium (NE) of our formulated resource allocation game not only exists but also is unique.

It is known that the global optimal solution for formulated resource allocation problem can be reached by the exhaustive searching for the optimal value in the subcarrier pairing indicator set (left {rho _{i}^{m,n}, forall i,m,nright }) and the amplification coefficient set (left {{beta _{i}^{n}}, forall i,nright }).

AIDmonitor gathers information from diverse databases to help users analyze ODA flows with a focus on Food Security, Nutrition, Agriculture and Rural Development, determine priorities for assistance and formulate resource mobilization strategies.

"Formulation" section formulates resource allocation as an optimization problem.

In this paper, we have formulated the resource allocation optimization problem for expanding service and increasing reliability of a grid computing system.

In this paper, we mathematically formulated the resource reallocation problem as an optimization problem with minimum network reconfiguration overhead subject to QoS requirements of the applications' flows.

The problem is formulated as resource constrained job shop scheduling problem, with operational safety constraints.

In the future, this will be improved to formulate the resource assignments via a bin packing problem formulation for more realistic results.

In this paper, we formulate the resource allocation problem as a bipartite matching problem.

In this paper, we formulate a resource allocation problem to find the optimal location of fixed measurement points and optimal sampling of probe trajectories to estimate NFD accounting for limited resources for data collection, network traffic heterogeneity and asymmetry in OD demand in a real-world network.

Using a time-variant mission-oriented WSN model, we formulate our resource allocation problem as a dynamic network utility maximization problem, which aims to maximize a hybrid mix of an aggregated objective function of missions' utilities and energy consumption, considering capacity, interference and sum-rate demand constraints.