Finding mimum of a function with 2 local mins

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The discussion centers on finding the minimum of a non-analytic function with two local minima using the steepest descent method. David highlights the challenge of selecting an appropriate starting point, as it affects the outcome of the minimum found. He seeks a reliable method to consistently identify the global minimum without prior knowledge of the function's peaks. The conversation emphasizes the need for numerical gradient techniques in optimization problems.

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I have a function that looks like this:
http://rpi.edu/~doriad/view1.jpg The function is non analytic, so I have to use something like the steepest descent method with numerical gradients to find the minimum. However, if my starting point is on the left of the tall peak, the min I find is on the left side (clearly) and if I choose the starting point to be on the right side I find the low point on the right. Clearly in this case I could just do both and take the smaller one, but if I'm not sure about the location of the tall peak to start with, I can't simply choose a starting point on either side. Is there a way to find the actual lowest point consistently?

Thanks,

David
 
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Hi David,

I think it would be a lot better if you could provide an image of the function to make it all much more clear.
 
The image has been posted.
Bump!
 

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