Global optimization scatter search

Optimization implies that the method moves in a useful direction, at least eventually. In using a local gradient method, one can check this property by evaluating local function values and gradients, both of which should decrease monotonically, at least near the solution. However, during a search for a global minimum, the clues about the multidimensional landscape are more scattered, so it helps to run a number of searches in parallel. The GA is a prime example of a parallel optimization method that searches many regions of parameter space simultaneously. 

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