Nested optimization teaser
- To: mathgroup at smc.vnet.net
- Subject: [mg46047] Nested optimization teaser
- From: "Joshua A. Solomon" <J.A.Solomon at city.ac.uk>
- Date: Tue, 3 Feb 2004 18:20:51 -0500 (EST)
- Sender: owner-wri-mathgroup at wolfram.com
Consider the toy identity function egg:
In[1]:= egg[in_]:=NMinimize[{(x-in)^2},{{x,-1,1}}][[2,1,2]]
In[2]:= egg[#]&/@{1,2,3}
Out[2]:= {1.,2.,3.}
Now then, clearly
In[3]:= NMinimize[(2-a)^2,a]
Out[3]:= {0.,{a->2.}}
However,
In[4]:= NMinimize[(2-egg[a])^2,a]
Out[4]:= {9.,{a->0}}
I know why this happens. What I don't know, is how to properly construct a
nested optimization so this doesn't happen. Specifically, how can I find the
minimum value (and the parameter values that produce it) of a function that
depends on the minimum value of another function, which, in turn, depends on
those same parameters?
js
--
Joshua A. Solomon
http://www.staff.city.ac.uk/~solomon