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These indices are the coefficients in the objective functions of an optimization model.
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Minimizing Hydrogen waste into fuel gas within the H2 network in a refinery is the objective function of an optimization problem in this paper.
But the objective function of an optimization problem is not always differentiable; therefore, the variational inequalities defined by the directional derivative are introduced.
Since the loss function can be viewed as the objective function of an unconstrained optimization problem, we will have to obtain P av numerically as a function of λ ̄.
The fundamental role of a type of an optimization criterion function is analyzed and a new effective criterion function is introduced.
Here, C x,a) is in fact a linear combination of loss functions (each quantifies an optimization concern).
In industrial practice, uncertainties are usually compensated for by using conservative decisions like an over-design of process equipment or an overestimation of operational parameters caused by worst case assumptions of the uncertain parameters, which leads to significant deterioration of the objective function in an optimization problem.
The PSO, with its efficient and adaptive search process provide near optimal solutions of an evaluation (fitness) function in an optimization problem and averts the FCM from trapping into local minima.
The enrichment of metabolic networks with stoichiometric coefficients (represented by edge weights) and the definition of an optimization function is a prerequisite for the constraint-based network analysis.
Consequently, the objective functions of the optimization problem can be clarified, specified and modeled.
We consider the problem of imputing the function that describes an optimization or equilibrium process from noisy partial observations of nearly optimal (possibly non-cooperative) decisions.
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