You might be interested in PROC PSMATCH, which uses a linear assignment solver under the hood for optimal matching:
https://go.documentation.sas.com/doc/en/pgmsascdc/v_065/statug/statug_psmatch_toc.htm
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You can impose an explicit "objective cut" constraint:
con NonnegativeCost:
cost >= 0;
But that will probably actually increase the solve time.
A more promising approach is to try different choices for the ALGORITHM= option. If you can share the SOLVE statement you are currently using, as well as the LP solver's iteration log, I might be able to give a more specific recommendation.
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The simplest way to get your code working is to make the following changes.
1. Change the declaration of two sets:
set <str> GUARDS;
set <str> SHIFTS;
2. Replace the READ DATA statement:
read data guard_availability into GUARDS=[Guard];
read data guard_availability into SHIFTS=[Shift];
read data guard_availability into DATES=[Date];
read data guard_availability into [Guard Shift Date]
Available Hours;
3. Change the CREATE DATA statement:
create data schedule from [Guard Shift Date] Assigned=x;
You might find this book of examples useful:
SAS Help Center: SAS/OR® User's Guide: Mathematical Programming Examples
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Sure. But that would lead to many combinations , here is one of combination:
DATA HAVE;
INPUT COURSE $ ROOM_NO $ ROOM_CAPACITY ROOM_LOAD;
DATALINES;
CHEM101 C101 20 7
CHEM101 C102 20 11
CHEM101 C103 10 8
CHEM101 C104 15 10
BIO302 HB102 22 20
BIO302 HB106 24 12
BIO302 HB902 30 29
BIO302 W102 30 31
BIO302 AB102 40 27
;
RUN;
%macro room(course=);
data temp;
set have;
if COURSE="&course.";
run;
proc optmodel;
set <str> ROOM_NO;
num ROOM_CAPACITY{ROOM_NO};
num ROOM_LOAD{ROOM_NO};
num sum_ROOM_LOAD=sum{i in ROOM_NO} ROOM_LOAD[i];
read data temp into ROOM_NO=[ROOM_NO] ROOM_CAPACITY ROOM_LOAD;
var v{ROOM_NO} binary;
min TotalCost = (sum{i in ROOM_NO} ROOM_CAPACITY[i]*v[i]) - sum_ROOM_LOAD ;
con con: sum{i in ROOM_NO} ROOM_CAPACITY[i]*v[i] >= sum_ROOM_LOAD;
solve ;
create data want from [ROOM]={i in ROOM_NO}
ROOM_CAPACITY=ROOM_CAPACITY[i]
ROOM_LOAD=ROOM_LOAD[i]
flag=v[i].sol;
quit;
data want;
length COURSE ROOM $ 80;
set want;
COURSE="&course.";
run;
proc append base=final_want data=want force;run;
%mend;
proc freq data=have noprint ;
table course/out=course;
run;
proc delete data=final_want;run;
data _null_;
set course;
call execute(catt('%room(course=',course,')'));
run;
proc summary data=final_want ;
by course;
var room_load;
output out=sum(drop=_:) sum=sum;
run;
data final_want2;
merge final_want sum;
by course;
if first.course then cum_ROOM_CAPACITY=0;
new_room_load=0;
if flag=1 then do;
cum_ROOM_CAPACITY+ROOM_CAPACITY;
new_room_load=ifn(sum>=cum_ROOM_CAPACITY,ROOM_CAPACITY,ROOM_CAPACITY-cum_ROOM_CAPACITY+sum);
end;
drop sum cum_ROOM_CAPACITY;
run;
proc print data=final_want2 noobs;run;
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Looks like you just need to read the correct data set:
/*read data WORK.SANTANDER_HIST into [date ativo] {j in PERIODS} <hist_data[date,ativo,j]=col(j)>;*/
read data WORK.SANTANDER_HIST_3 into [date ativo] {j in PERIODS} <hist_data[date,ativo,j]=col(j)>;
With this change, the ERROR messages no longer appear.
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RobPratt,
Unfortunately, The OPTBINNING procedure is running under SAS/Viya , I don't have it. My sas is a stand-alone PC version.
And it looks like PROC OPTBINNING need set up some parameters(cutpoints ,woe,lower bound, upper bound, and WOE trend <-- what does it mean? ) firstly .
I need the code like your posted before for binning categroy variable .Like smoothing and flexibility.
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proc optmodel;
num a{1..2}=[2 12];
num b{1..3}=[2 12 24];
num d{i in 1..10}=i;
num e{i in 1..47}=i;
var var_a{1..2} binary;
var var_b{1..3} binary;
var var_c >=2 <=42 ;
var var_d integer;
impvar sum= 4*sum{i in 1..2} a[i]*var_a[i] +
-2*sum{i in 1..3} b[i]*var_b[i] +
-2*var_c +
4*var_d ;
min obj=sum;
con con_total:sum>=1;
con con_a:sum{i in 1..2} var_a[i]=1;
con con_b:sum{i in 1..3} var_b[i]=1;
con con_d:var_c=2+4*var_d;
solve ;
print a var_a ;
print b var_b ;
print var_c ;
print var_d ;
quit;
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I see. Thank you very much for the explanation where the error comes from. I will take a look at the sparse modelling. I was just trying to allocate the pair of distance < 30 to one proc optmodel and the pair of distance > 30 to another pro optmodel code. This was just the idea. But I think this is not the right logic or not applicable in SAS.
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Can you pls explain if the situation is as follows; there are two types of staff models One paid for the hours worked and how they reach the site do not matter One is paid for the hours worked (more efficient than model 1) and the travelling time from the previous working location where a VRP should be applied. the final solution should be a mix of both models there is no data on the total number of staff available Our objective is to maximise the profit How would the code change??
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