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Yen et al. [48] utilized the simplex method to conduct a crossover operation among individuals so as to produce new ones along the evolutionary direction.
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We chose to use the simplex method of [15], since it was already available in Matlab, via the "fminsearch" function.
To illustrate the simplex method, the example from the preceding section will be solved again.
The simplex method is a systematic procedure for testing the vertices as possible solutions.
The simplex method is one of the most useful and efficient algorithms ever invented, and it is still the standard method employed on computers to solve optimization problems.
In 1947 a method (described in the section The simplex method) was introduced that turned out to solve practical problems efficiently.
The activity coefficients are obtained by the simplex method.
Moreover, if we use a classical simplex method, we can perform really badly since the worst-case complexity of the simplex method has exponential time.
In general, the neural network method was more accurate than the simplex method.
Note that for the "Simplex method", ABIC value plots are color-coded, and larger symbols indicate greater iteration number of the simplex optimization process.
We solve (2.7) or (2.8) in the optimization step by the simplex method (see [19]).
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