It would in the stictess sense be non-linear since it is only defined for 
descrete interface values for each variable. And in general it would be 
non-linear anyway. If I only have three variables which can take on values 
1,2,3 then f(1,2,3) could equal 0 and f(2,1,3) could equal 10.

Thank you for the suggestions.

Kevin

---- Paul Smith <phh...@gmail.com> wrote: 
> On Sun, Mar 29, 2009 at 9:45 PM,  <rkevinbur...@charter.net> wrote:
> > I have an optimization question that I was hoping to get some suggestions 
> > on how best to go about sovling it. I would think there is probably a 
> > package that addresses this problem.
> >
> > This is an ordering optimzation problem. Best to describe it with a simple 
> > example. Say I have 100 "bins" each with a ball in it numbered from 1 to 
> > 100. Each bin can only hold one ball. This optimization is that I have a 
> > function 'f' that this array of bins and returns a number. The number 
> > returned from f(1,2,3,4....) would return a different number from that of 
> > f(2,1,3,4....). The optimization is finding the optimum order of these 
> > balls so as to produce a minimum value from 'f'.I cannot use the regular 
> > 'optim' algorithms because a) the values are discrete, and b) the values 
> > are dependent ie. when the "variable" representing the bin location is 
> > changed (in this example a new ball is put there) the existing ball will 
> > need to be moved to another bin (probably swapping positions), and c) each 
> > "variable" is constrained, in the example above the only allowable values 
> > are integers from 1-100. So the problem becomes finding the optimum order 
> > of the "balls".
> >
> > Any suggestions?
> 
> If your function f is linear, then you can use lpSolve.
> 
> Paul
> 
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