Hi,

 a bit like

https://www.ibm.com/developerworks/community/forums/html/topic?id=2bbb5d8a-b968-44ff-b4e7-4f9089f4b694&ps=25

but with CPO

Let us take a RCPSP example

.mod

 using CP;
 
 int n=30; // number of random seeds
int d[1..n]; // duration
int o[1..n]; // objective
int iter[1..n]; // iterations

execute
{
cp.param.LogVerbosity="Quiet";
}

int NbTasks = ...;
int NbRsrcs = ...;

range RsrcIds = 0..NbRsrcs-1;

int Capacity[r in RsrcIds] = ...;

tuple Task {
  key int id;
  int     pt;
  int     dmds[RsrcIds];
  {int}   succs;
}

{Task} Tasks = ...;

dvar interval itvs[t in Tasks]  size t.pt;

cumulFunction rsrcUsage[r in RsrcIds] =
  sum (t in Tasks: t.dmds[r]>0) pulse(itvs[t], t.dmds[r]);

execute {
        cp.param.TimeLimit = 0.1;
}

minimize max(t in Tasks) endOf(itvs[t]);
subject to {
  forall (r in RsrcIds)
    rsrcUsage[r] <= Capacity[r];
  forall (t1 in Tasks, t2id in t1.succs)
    endBeforeStart(itvs[t1], itvs[<t2id>]);
}

execute {
  for (var t in Tasks) {
    writeln("Task " + t.id + " starts at " + itvs[t].start);
  }
}

main {

//thisOplModel.generate();

var sum_d=0;
var sum_o=0;;
var sum_iter=0;

writeln("seed objective branches   runtime");

for(var i=1;i<=thisOplModel.n;i++)
{

    var opl=new IloOplModel(thisOplModel.modelDefinition);
    var data = thisOplModel.dataElements;
    opl.addDataSource(data);
    
    opl.generate();

    cp.param.randomseed=i;

    
    
    
    var d1=new Date();
    cp.solve();
    var d2=new Date();
    
    thisOplModel.d[i]=d2-d1;
    sum_d+=d2-d1;
    thisOplModel.d[i]=d2-d1;
    thisOplModel.o[i]=Opl.ftoi(Opl.round(cp.getObjValue()));
    sum_o+=thisOplModel.o[i];
    thisOplModel.iter[i]=cp.info.NumberOfBranches;
    sum_iter+=thisOplModel.iter[i];
    writeln(i,"    ",thisOplModel.o[i],"     ",thisOplModel.iter[i],"       ",
    thisOplModel.d[i]/1000);
    cp.clearModel();
}    

writeln("-----------------------------------------");
writeln("average      ",sum_o/thisOplModel.n," ",
sum_iter/thisOplModel.n," ",sum_d/thisOplModel.n/1000);
writeln("std dev      ",Opl.standardDeviation(thisOplModel.o),"     ",
Opl.standardDeviation(thisOplModel.iter),"     ",Opl.standardDeviation(thisOplModel.d)/1000);

}
 

.dat

NbTasks = 122;
NbRsrcs = 4;

Capacity = [ 12, 12, 11, 12 ];

Tasks = {
  < 1, 0, [ 0, 0, 0, 0 ], { 2, 3, 4 } >,
  < 2, 8, [ 0, 10, 0, 0 ], { 40, 48, 61 } >,
  < 3, 5, [ 7, 0, 0, 0 ], { 19, 34, 46 } >,
  < 4, 3, [ 2, 0, 0, 0 ], { 5, 10, 11 } >,
  < 5, 10, [ 0, 0, 8, 0 ], { 6, 13, 32 } >,
  < 6, 9, [ 0, 10, 0, 0 ], { 7, 8, 20 } >,
  < 7, 10, [ 0, 0, 3, 0 ], { 29, 33, 70 } >,
  < 8, 10, [ 1, 0, 0, 0 ], { 9, 12, 16 } >,
  < 9, 5, [ 0, 0, 0, 9 ], { 14, 18, 39 } >,
  < 10, 2, [ 0, 0, 6, 0 ], { 22, 63 } >,
  < 11, 10, [ 4, 0, 0, 0 ], { 48, 58, 117 } >,
  < 12, 2, [ 0, 0, 6, 0 ], { 24, 28, 30 } >,
  < 13, 4, [ 6, 0, 0, 0 ], { 51, 61 } >,
  < 14, 6, [ 6, 0, 0, 0 ], { 15, 61, 110 } >,
  < 15, 7, [ 6, 0, 0, 0 ], { 49, 107 } >,
  < 16, 1, [ 0, 0, 2, 0 ], { 17, 41, 89 } >,
  < 17, 10, [ 0, 0, 0, 5 ], { 40, 64, 80 } >,
  < 18, 9, [ 0, 3, 0, 0 ], { 21, 23, 65 } >,
  < 19, 10, [ 0, 0, 0, 10 ], { 45, 58, 89 } >,
  < 20, 5, [ 7, 0, 0, 0 ], { 29, 37, 43 } >,
  < 21, 1, [ 0, 4, 0, 0 ], { 26, 35, 50 } >,
  < 22, 1, [ 0, 0, 0, 8 ], { 72, 95 } >,
  < 23, 9, [ 1, 0, 0, 0 ], { 57, 63, 73 } >,
  < 24, 10, [ 0, 6, 0, 0 ], { 25, 27, 43 } >,
  < 25, 4, [ 10, 0, 0, 0 ], { 67, 75, 91 } >,
  < 26, 10, [ 0, 0, 8, 0 ], { 36, 71 } >,
  < 27, 6, [ 0, 0, 4, 0 ], { 35 } >,
  < 28, 1, [ 3, 0, 0, 0 ], { 35, 66, 105 } >,
  < 29, 8, [ 0, 0, 0, 6 ], { 108 } >,
  < 30, 5, [ 0, 0, 6, 0 ], { 31, 33, 80 } >,
  < 31, 3, [ 0, 0, 0, 2 ], { 44, 52, 97 } >,
  < 32, 6, [ 10, 0, 0, 0 ], { 47, 67, 82 } >,
  < 33, 2, [ 0, 0, 0, 8 ], { 68, 78, 103 } >,
  < 34, 7, [ 0, 0, 0, 3 ], { 87, 94, 99 } >,
  < 35, 9, [ 0, 0, 3, 0 ], { 47, 56, 90 } >,
  < 36, 5, [ 5, 0, 0, 0 ], { 112 } >,
  < 37, 10, [ 0, 0, 5, 0 ], { 38, 51, 102 } >,
  < 38, 3, [ 7, 0, 0, 0 ], { 119 } >,
  < 39, 2, [ 0, 0, 6, 0 ], { 41, 62, 81 } >,
  < 40, 9, [ 0, 9, 0, 0 ], { 42, 75 } >,
  < 41, 6, [ 0, 1, 0, 0 ], { 57, 66 } >,
  < 42, 3, [ 0, 0, 0, 10 ], { 49, 83, 92 } >,
  < 43, 3, [ 0, 3, 0, 0 ], { 81 } >,
  < 44, 7, [ 8, 0, 0, 0 ], { 49, 74, 92 } >,
  < 45, 1, [ 0, 0, 0, 5 ], { 77 } >,
  < 46, 1, [ 0, 1, 0, 0 ], { 56, 69, 83 } >,
  < 47, 7, [ 10, 0, 0, 0 ], { 104 } >,
  < 48, 5, [ 0, 3, 0, 0 ], { 53, 56, 59 } >,
  < 49, 8, [ 0, 1, 0, 0 ], { 53, 108 } >,
  < 50, 7, [ 0, 0, 7, 0 ], { 53, 54, 60 } >,
  < 51, 1, [ 0, 0, 0, 2 ], { 52, 55, 71 } >,
  < 52, 2, [ 5, 0, 0, 0 ], { 59, 63, 75 } >,
  < 53, 1, [ 0, 0, 0, 3 ], { 102 } >,
  < 54, 4, [ 0, 0, 0, 7 ], { 55, 76, 78 } >,
  < 55, 7, [ 0, 0, 4, 0 ], { 58, 68, 83 } >,
  < 56, 10, [ 0, 0, 2, 0 ], { 62 } >,
  < 57, 9, [ 0, 0, 1, 0 ], { 69, 90 } >,
  < 58, 1, [ 0, 0, 0, 7 ], { 72, 104 } >,
  < 59, 8, [ 0, 0, 1, 0 ], { 62, 70, 113 } >,
  < 60, 1, [ 0, 6, 0, 0 ], { 66, 70, 86 } >,
  < 61, 4, [ 0, 0, 0, 7 ], { 73, 84, 93 } >,
  < 62, 2, [ 0, 0, 0, 1 ], { 72, 87, 88 } >,
  < 63, 8, [ 1, 0, 0, 0 ], { 68, 78 } >,
  < 64, 6, [ 8, 0, 0, 0 ], { 74, 95, 98 } >,
  < 65, 7, [ 0, 9, 0, 0 ], { 77, 88, 105 } >,
  < 66, 2, [ 0, 9, 0, 0 ], { 79, 106 } >,
  < 67, 5, [ 6, 0, 0, 0 ], { 77, 93, 94 } >,
  < 68, 6, [ 0, 0, 0, 6 ], { 84, 85, 99 } >,
  < 69, 4, [ 0, 3, 0, 0 ], { 93, 108 } >,
  < 70, 3, [ 0, 10, 0, 0 ], { 115 } >,
  < 71, 9, [ 0, 0, 0, 1 ], { 79, 86, 114 } >,
  < 72, 4, [ 0, 0, 0, 8 ], { 110 } >,
  < 73, 1, [ 0, 5, 0, 0 ], { 74, 79, 100 } >,
  < 74, 3, [ 1, 0, 0, 0 ], { 82, 85 } >,
  < 75, 9, [ 0, 9, 0, 0 ], { 87, 88, 101 } >,
  < 76, 4, [ 0, 0, 9, 0 ], { 80, 90 } >,
  < 77, 2, [ 7, 0, 0, 0 ], { 85, 98 } >,
  < 78, 8, [ 0, 0, 0, 8 ], { 84, 105 } >,
  < 79, 9, [ 0, 0, 2, 0 ], { 91, 92 } >,
  < 80, 10, [ 0, 0, 0, 7 ], { 81, 91, 103 } >,
  < 81, 8, [ 0, 4, 0, 0 ], { 82 } >,
  < 82, 6, [ 0, 10, 0, 0 ], { 101 } >,
  < 83, 2, [ 0, 0, 3, 0 ], { 94, 95 } >,
  < 84, 5, [ 0, 2, 0, 0 ], { 86, 100 } >,
  < 85, 5, [ 8, 0, 0, 0 ], { 101 } >,
  < 86, 5, [ 8, 0, 0, 0 ], { 89, 107, 111 } >,
  < 87, 2, [ 0, 0, 0, 4 ], { 109 } >,
  < 88, 2, [ 0, 0, 8, 0 ], { 115 } >,
  < 89, 10, [ 0, 0, 0, 7 ], { 109 } >,
  < 90, 6, [ 0, 0, 0, 2 ], { 98, 110, 111 } >,
  < 91, 2, [ 7, 0, 0, 0 ], { 96, 99 } >,
  < 92, 2, [ 0, 0, 0, 6 ], { 96, 103, 116 } >,
  < 93, 8, [ 1, 0, 0, 0 ], { 97, 117 } >,
  < 94, 5, [ 0, 6, 0, 0 ], { 96 } >,
  < 95, 7, [ 5, 0, 0, 0 ], { 97, 119 } >,
  < 96, 10, [ 0, 4, 0, 0 ], { 111, 118 } >,
  < 97, 3, [ 0, 0, 0, 1 ], { 104 } >,
  < 98, 8, [ 0, 6, 0, 0 ], { 100, 102, 107 } >,
  < 99, 1, [ 0, 0, 0, 4 ], { 121 } >,
  < 100, 9, [ 0, 6, 0, 0 ], { 106 } >,
  < 101, 7, [ 0, 0, 0, 10 ], { 118 } >,
  < 102, 1, [ 0, 5, 0, 0 ], { 113 } >,
  < 103, 10, [ 0, 0, 0, 2 ], { 112 } >,
  < 104, 1, [ 0, 0, 0, 4 ], { 106 } >,
  < 105, 1, [ 0, 0, 0, 4 ], { 113 } >,
  < 106, 2, [ 0, 0, 0, 6 ], { 114 } >,
  < 107, 9, [ 0, 0, 0, 2 ], { 109 } >,
  < 108, 2, [ 0, 2, 0, 0 ], { 121 } >,
  < 109, 7, [ 0, 4, 0, 0 ], { 118 } >,
  < 110, 4, [ 0, 0, 6, 0 ], { 112, 116 } >,
  < 111, 6, [ 0, 0, 7, 0 ], { 117, 119 } >,
  < 112, 1, [ 0, 8, 0, 0 ], { 120 } >,
  < 113, 6, [ 0, 0, 0, 10 ], { 114 } >,
  < 114, 5, [ 0, 6, 0, 0 ], { 115 } >,
  < 115, 6, [ 9, 0, 0, 0 ], { 116 } >,
  < 116, 1, [ 0, 0, 0, 7 ], { 120 } >,
  < 117, 9, [ 0, 0, 0, 8 ], { 120 } >,
  < 118, 7, [ 0, 0, 0, 9 ], { 121 } >,
  < 119, 5, [ 0, 0, 10, 0 ], { 122 } >,
  < 120, 4, [ 0, 0, 0, 6 ], { 122 } >,
  < 121, 10, [ 0, 0, 8, 0 ], { 122 } >,
  < 122, 0, [ 0, 0, 0, 0 ], {  } >
 };

gives

seed objective branches   runtime
1    146     42438       0.111
2    146     42957       0.107
3    146     44281       0.106
4    146     43253       0.107
5    144     46651       0.108
6    145     50591       0.109
7    145     49176       0.106
8    145     49815       0.106
9    144     49871       0.108
10    144     50600       0.107
11    144     50491       0.107
12    145     51246       0.108
13    144     47336       0.107
14    143     47893       0.11
15    144     44036       0.107
16    144     49669       0.108
17    146     43558       0.107
18    145     48943       0.106
19    145     49549       0.107
20    141     47410       0.108
21    145     47841       0.108
22    143     51447       0.107
23    144     51109       0.107
24    146     46076       0.107
25    145     51643       0.106
26    145     44914       0.107
27    144     44453       0.109
28    145     53116       0.106
29    144     51382       0.107
30    145     47474       0.111
-----------------------------------------
average      144.6 47973.966666667 0.1075
std dev      1.083205121     3020.943698949     0.001335415

regards

PS:

Evaluating CPO random seed variability will increase confidence.