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A function can have several local maxima, not all of which are overall ("global") maxima.
A decrease of about 77.3% in the number of generations required to reach the global maxima is also witnessed.
This allows both sides to take more risks, investing time and resources to find global maxima rather than simply seeking local peaks.
We show how to use this algorithm to find global maxima of non-convex multivariate functions in separated form.
Results of these calculations are represented in the form of NPV Net Present Valuee) surfaces and NPV distributions which naturally locate global maxima for different starting flow rates.
The extreme response distributions conditional on wind speeds are determined from the simulation data using global maxima method and random process model method.
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The loglikelihood function is globally concave, and hence a global maximum exists.
--find the global maximum and you're done.
A combined global maximum dissipation principle is shown to hold.
I'm going to find the global maximum on column j.
The value V0 is a global threshold and set to 0.3 times the global maximum of the filtered heatmap.
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