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We formulate the capacity allocation process as a bi-objective optimization problem, in which the decision maker seeks to increase the mean productivity of the entire array while having control on the variability of the aggregate energy supply.
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The objective of this paper is to formulate the capacities and boundary conditions of the rail structure interaction by means of extended numerical linear and nonlinear analyses, which are not fully comprehended in the standard specifications and therefore result in conservative interaction laws.
The study formulates the capacity addition problem as a mixed-integer network design problem.
In this paper, we have formulated the capacity expansion with the combined road pricing problem as a bi-level program, where the upper level optimizes the link capacity expansion vector and maximizes the social welfare, while the lower level determines the demand and the flow satisfying the Wardrop principles.
Based on this wideband sensing approach, we further formulate the network capacity optimization problem with the guaranteed PU link rate, and derive the corresponding optimum threshold.
Telatar [2] and Foschini [3] first formulated the system capacity of the MIMO systems assuming independent and identically distributed fading at different antennas.
From this, we can formulate the resource allocation with capacity constraints of the feedback channels.
In Section 3, we build the distance-dependent interference model and formulate the problem of network capacity optimization.
Subsequently, we formulate the problem of maximizing sum capacity while satisfying the minimum capacity requirements for each femtocell.
Now, we can formulate the outage throughput maximization under feedback capacity constraints: (9).
We formulate the combined road toll pricing and capacity expansion problem as a bi-level programming problem under budget constraints.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com