Originally posted by: Humblor

Hello,

I have a model as attached below. 

I have two objectives:

minimize R as : dexpr float R = (sum(s in Facility,c in Customers,i in ProductsdRawMat,t in Periods) -(shortCost[c][i]*Supply[s][c][i][t]));

minimize C as : dexpr float C = (sum(s in Facility,j in Processors,i in ProductsdRawMat,t in Periods) VarCost[s][j][i]*ProdAmt[s][j][i][t]) + (sum(s in Facility1,i in RawMat,t in Periods) Price[s][i]*Consum[s][i][t]) + (sum(s in Facility,i in ProductsdRawMat,t in Periods) hCost[s][i][t]*InvLev[s][i][t]) + (sum(s in Facility,c in Customers,i in ProductsdRawMat,t in Periods) transCost1[s][c]*Supply[s][c][i][t]) + (sum(s in Facility1,sd in Facility2,i in IntProd,t in Periods) transCostF[s][sd]*FlowInt[s][sd][i][t]) + (sum(s in Facility,i in ProductsdRawMat,t in Periods) zetaCost[s][i]*InvDev[s][i][t] ) + (sum(c in Customers,i in ProductsdRawMat,t in Periods) shortCost[c][i]*InvShort[c][i][t] );

I want to apply epsilon constraint keeping minimize C as objective and R in the constraint.

I have found the range of R as: -12059710.183892<=R<=0;

Can someone please tell me a code in CPLEX how to get the Pareto front from the efficient solutions obtained using multiple runs.

I would be really grateful if someone helps me very soon. I am in urgent need to present my report.

Thanks a lot.

Regards.

Hi,

You may read and adapt

https://www.ibm.com/developerworks/community/forums/html/topic?id=d429f881-12ee-4d34-92a1-6344fceba623&ps=25

regards