How do I solve a series of different random problems with data drawn from the same distribution?

AMPL > >Files and Preprocessing > >How do I solve a series of different random problems with data drawn from the same distribution?

Use AMPL’s reset data command to resample from all of the random-valued functions in the model. For example, in model steel4.mod from the AMPL book, suppose that parameter avail is changed so that its value is given by a random function:

param avail_mean {STAGE} >= 0;
param avail_variance {STAGE} >= 0;
param avail {s in STAGE} :=
        Normal (avail_mean[s], avail_variance[s]);

with corresponding data

param:   avail_mean avail_variance :=
  reheat     35         5
  roll       40         2 ;

Then AMPL will take new samples from the Normal distribution after each reset data:

ampl: model steel4.mod;
ampl: data steel4.dat;
ampl: solve;
MINOS 5.4: optimal solution found.
3 iterations, objective 187632.2489
avail [*] :=
reheat  32.3504
  roll  43.038
;
ampl: reset data avail;
ampl: solve;
MINOS 5.4: optimal solution found.
4 iterations, objective 158882.901
ampl: display avail;
avail [*] :=
reheat  32.0306
  roll  32.6855
;

Using this feature together with one of AMPL’s looping commands, you can automatically solve a series of random realizations from the model, and summarize the results:

model steel4.mod;
data steel4.dat;
param nruns := 5;
param optvalue {1..nruns};
for {k in 1..nruns} {
   reset data avail;
   solve;
   let optvalue[k] := Total_Profit;
}
display (sum {k in 1..nruns} optvalue[k]) / nruns;

If you use reset rather than reset data, then AMPL’s random number generator is reset, and the values of avail repeat from the beginning. To get a different sequence of random numbers from the generator, you must change the random number seed; give the command option randseed n — where n is a positive integer — or option randseed 0 to have AMPL choose a seed based on the system clock.

Posted in: Files and Preprocessing