Hi Here is simple example that I hope illustrates my optimisation problem. Multiple offers per customers. Key issue for me is that I am not familiar with optmodel and I am struggling to structure it correctly. Would be great is someone could help on this. I have included my existing optmodel syntax but this is far from finish. I am sure this can not be difficult. data opti1; do i=1 to 250000; do k=1 to 5; custid=i+1000; offer_code=round((ranuni(849)*50),1); conflict_group=round((offer_code),10)/10; ranking=round(ranuni(745)*100,1); output; end; end; drop k i; run; /*objective = maximize sum of ranking over all selected offers and customers; constrain not more than 3 offers per customer; constrain not more than one offer per customer from the same conflict group. same output code always maps to same conflict group; Customers will be rank ordered using their max ranking of allocated offers. Within top 100k of customers we would like to be able to put a constrains on volumes for offers and/or conflict group - i.e. min volume for conflict group 5 = 20000 and min volume for offer 23= 5000 and max volume for conflict group 0 = 25000;*/ proc optmodel; set <str,str> CUST_camp; num ranking {CUST_camp}; num conflict_group {CUST_camp}; read data opti1 into CUST_camp=[custid offer_code] ranking conflict_group; set <str> CUST; read data opti2 into CUST=[custid]; var assign{cust_camp} binary; *constrain 1- max 2 offers per customer; con cust_max_con {i in cust}: sum {<(i),j> in cust_camp} assign[i,j] <=2; *not more than 2 per custid; /* *constrain 1- 2 selected offers per custid can not be in the same conflict group; con cust_conflict {i in cust}: ((setof{<(i),j> in cust_camp} conflict_group[i,j] * assign[i,j]) inter (setof{<(i),j> in cust_camp} conflict_group[i,j] * assign[i,j]))={0}; */ max response=sum {<i,j> in cust_camp} ranking[i,j] * assign[i,j]; solve with milp; quit;
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