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This method is able to provide only one solution point for estimation of sediment amount.
Gradient based methods, such as Normal Boundary Intersection (NBI), for solving a MOP require solving at least one optimization problem for each solution point.
Factors affecting the dual consistency, such as the solution point distribution, correction functions, boundary conditions and the discretization approach for the non-linear flux divergence term, are studied.
The basic requirements are contending claims from mathematical physical description and the numerical solution point of view on the other side.
Mass spectrometric cyclic voltammograms (MSCVs) and IR spectra, acquired with the alcohol in the solution, point out the formation of CO2 and crotonaldehyde as oxidation products.
For this purpose, we propose to model metabolic networks through classical optimization formulations, such as the classical S-system representation, with an additional constraint to enforce stability within a prespecified neighborhood of the solution point.
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Therefore, we derive particular sets of nonuniform solution points and quadrature weights near the domain boundaries.
The optimal input control factor values are no longer restricted to solution points composed of discrete experimental levels.
We give a single-exponential time method for finding all the isolated solution points of a system of polynomials, even in the presence of infinitely many solutions at infinity or elsewhere.
On the other hand, genetic algorithms (GAs) can produce more than one solution points providing optimal relation between discharge and sediment loads.
A pair-wise solution points is used for crossover and a new set of solution points is obtained.
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