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Because (mathbb {C}(E,nu), G_{mathrm {c}}, boldsymbol {Gamma }(gamma _{1}, gamma _{2})) are independent of each other we can define and minimize cost function for each set of constants separately.
The Restricted Neighborhood Search Clustering Algorithm RNSCC) is a cost based local search algorithm to explore the solution space to minimize cost function, calculated according to the numbers of intra-cluster and inter-cluster edges [12].
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Nevertheless, schemes that seek to minimize cost functions similar to Eq. (10) have proven useful in operational meteorology (see [ 15] and references therein for an extensive bibliography).
In this paper, we address the challenge of overlay topology design by considering which overlay topology best minimizes cost function, taking into account overlay link creation cost and routing cost.
We consider the least squares parameter estimation problem that amounts to minimizing cost functions of the form (9) with respect to p, where the y i (t j ) are the measured or simulated data introduced in equation (2).
The objective of this graph-based approach is thus not simply to minimize the cost function, but to minimize the cost function conditional on the proposed new clustering.
Since two unknown variables exist in equation (11), an alternating minimization scheme is used to minimize the cost function (11).
Based on the reference path, an optimal controller is designed to minimize the cost function.
These techniques minimize a cost function by exploring an application parameter search space.
They are formulated as optimization problems, seeking values for the model's inputs that minimize a cost function measuring departures from steady state and from date.
Traditionally for these problems, the objective function is to minimize a cost function while satisfying the reliability constraints.
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