Examples of using The objective function in English and their translations into Spanish
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Change in the objective function value was less than options.
We are to find the maximum(not minimum) value of the objective function.
Change the sign of the objective function for a minimization problem.
The objective function was to minimize the unit cost of the product.
Attempts to develop the objective function may fail.
The objective function is different if we are in a regulated electricity system to whether we are in a liberalized system.
X, fval= fminimax(…) returns the value of the objective function fun at the solution x.
In NLLSQ the objective function is quadratic with respect to the parameters only in a region close to its minimum value, where the truncated Taylor series is a good approximation to the model.
If the objective function is concave(maximization problem), or convex(minimization problem) and the constraint set is convex, then the program is called convex and general methods from convex optimization can be used in most cases.
Predicted decrease in the objective function was less than the FunctionTolerance tolerance.
Here the model is linear, the objective function is the expected value of a quadratic form, and the disturbances are purely additive.
However, the authors also noted that the current implementation of TISVPA had some difficulties combining the various components of the objective function, as is currently done with CASAL.
Quadratic programming allows the objective function to have quadratic terms, while the feasible set must be specified with linear equalities and inequalities.
In this case σ2 is approximated by σ 2 U n d- n p{\displaystyle\sigma^{2}={\frac{U}{n_{\mathrm{d}}-n_{\mathrm{p}}}}}where U is the minimum value of the objective function and nd and np are the number of data and parameters, respectively.
Constraint satisfaction studies the case in which the objective function f is constant this is used in artificial intelligence, particularly in automated reasoning.
Most often only the diagonal elements are known,in which case the objective function simplifies to U∑ i W i i r i 2{\displaystyle U=\sum_{ i} W_{ ii} r_{ i}^{ 2}} with Wij 0 when j≠ i.
The objective function of the new society we are constructing includes providing for the growth of public well-being, a stable monetary system, a low unemployment rate and efficient environmental protection.
A linear programming problem seeks to optimize(find a maximum or minimum value)a function(called the objective function) subject to a number of constraints on the variables which, in general, are linear inequalities.
An example of this would be in the study of the carbohydrate metabolism pathways where the objective function would probably be defined as a certain proportion of ATP and NADH and thus simulate the production of high energy metabolites by this pathway.
Traditional envelope theorem derivations use the first-order condition for(1), which requires that the choice set X{\displaystyle X}have the convex and topological structure, and the objective function f{\displaystyle f} be differentiable in the variable x{\displaystyle x.
In some problems,often called constraint optimization problems, the objective function is actually the sum of cost functions, each of which penalizes the extent(if any) to which a soft constraint(a constraint which is preferred but not required to be satisfied) is violated.
Alternatively, if the constraints are all equality constraints and are all linear, they can be solved for some of the variables in terms of the others, andthe former can be substituted out of the objective function, leaving an unconstrained problem in a smaller number of variables.
Constraints can be either hard constraints, which set conditions for the variables that are required to be satisfied, orsoft constraints, which have some variable values that are penalized in the objective function if, and based on the extent that,the conditions on the variables are not satisfied.