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The mean risk index was used as an objective variable in heuristic optimisation.
We show that those aggregated multipliers are activated or neutralized by specific structures of the policy control and that no other outcome in the objective variable is reachable.
A psychophysical approach was applied to evaluate the thermal influence of a task chair with the seat pan temperature as the objective variable.
The models are constructed using monthly input variables, including air temperature (T-air), windspeed (W), relative humidity (RH), solar radiation (SR), while the objective variable is the soil temperature measurement at 5, 50 and 100 cm depths for the period 1986–2010.
Thereafter, the mean risk index was used as an objective variable in heuristic optimization in forest planning to demonstrate how the optimal cuttings and the spatial layout of the landscape may change depending on the wind and snow conditions and the support that trees provide to each other.
The objective variable was NPV, calculated to infinity with a 3% discount rate.
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We also propose an objective variable-based regionalization approach by combining the rotated empirical orthogonal function (REOF) method and K-means clustering analysis, to determine homogeneous regions effectively for such a large volume of daily grid data.
The objective variables obviously are at project level and then at brand level top-line and bottom-level top-line
One obvious solution is to set the objective variables x1 = x2 = 0, which corresponds to the extreme point at the origin.
In the primal problem the objective is replaced by the product (px) of a vector x = (x1, x2, x3, …, xn T, whose components are the objective variables and where the superscript "transpose" symbol indicates that the vector should be written vertically, and another vector p = (p1, p2, p3, …, pn), whose components are the coefficients of each of the objective variables.
If one of the objective variables is increased from zero while the other one is fixed at zero, the objective value x0 will increase as desired (subject to the slack variables satisfying the equality constraints).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com