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This Warning often appears for option "decomp=concomp" as you use it. You should have special structure of constraints and data for this option.  https://support.sas.com/documentation/onlinedoc/or/143/decomp.pdf#page=6&zoom=100,96,457 I would recommend you to use "auto". That's more valuable in regular problems. If talk about your goals to create logic for CYSSpecific and CFSSpecific, you can add some binary variables to creating if-else expressions. Thas most interesting job in MILP. It can looks like that:  Binary x, If a>b then x=0, else x=1. This approach use BigM trick. ... View more

Hi Santha, I've saw your code and could highlight some moment: var BoxesNeeded {LegitCombo_ISN} >= 0 integer; var Proportion {LegitCombo_ISN} >= 0 <= 1; impvar VolumeInsideBox {i in ISN, b in BOX,m in MOL,d in T1,w in T2} = Volume_ISN[i] * Proportion[i,b,m,d,w]; impvar WeightInsideBox {i in ISN, b in BOX,m in MOL,d in T1,w in T2} = Weight_ISN[i] * Proportion[i,b,m,d,w]; In this case, you'll get some errors because you create variables only for certain subset with expression Flag=1. I would recommend you to fix some values for variable, like that: var BoxesNeeded {i in ISN, b in BOX,m in MOL,d in T1,w in T2} >= 0 integer; var Proportion {i in ISN, b in BOX,m in MOL,d in T1,w in T2} >= 0 <= 1; for {i in ISN, b in BOX,m in MOL,d in T1,w in T2:  Flag[i,b,m,d,w]=1 } do;         fix BoxesNeeded {i in ISN, b in BOX,m in MOL,d in T1,w in T2}=0;         fix Proportion {i in ISN, b in BOX,m in MOL,d in T1,w in T2}=0; end; In this case you can set constraint correctly. Thats should be look like that: con CYSSpecific {m in MOL, i in ISN,d in T1: m="CYS"}: sum {b in BOX, w in T2} VolumeInsideBox[i,b,m,d,w]= Volume_ISN[i]*Is_ISN_MOL[i,m]; ... View more

Thank you for explanation Rob! ... View more

Hi Rob Thank you for response. Here two different problems, sure. My main point about method. You provided solutions for MILP initially. For MILP, this task will be very unpleasant) I would use network or local search solver. ... View more

Hi   You also can use network solver for TSP. This approach more efficient.   data Cities; input city $20. lat long; datalines; Albany, NY 42.652552778 -73.75732222 Annapolis, MD 38.978611111 -76.49111111 Atlanta, GA 33.749272222 -84.38826111 Augusta, ME 44.307236111 -69.78167778 Austin, TX 30.274722222 -97.74055556 Baton Rouge, LA 30.457072222 -91.18740556 Bismarck, ND 46.820813889 -100.7827417 Boise, ID 43.617697222 -116.1996139 Boston, MA 42.357708333 -71.06356389 Carson City, NV 39.164075 -119.7662917 Charleston, WV 38.336388889 -81.61222222 Cheyenne, WY 41.140277778 -104.8197222 Columbia, SC 34.000433333 -81.03314722 Columbus, OH 39.961388889 -82.99888889 Concord, NH 43.206747222 -71.53812778 Denver, CO 39.739094444 -104.9848972 Des Moines, IA 41.591177778 -93.60386944 Dover, DE 39.157305556 -75.51972222 Frankfort, KY 38.186777778 -84.87533333 Harrisburg, PA 40.264444444 -76.86666667 Hartford, CT 41.764136111 -72.68277778 Helena, MT 46.5857 -112.0184 Indianapolis, IN 39.768611111 -86.1625 Jackson, MS 32.303888889 -90.18222222 Jefferson City, MO 38.579119444 -92.17299167 Lansing, MI 42.733727778 -84.55558889 Lincoln, NE 40.808088889 -96.69958611 Little Rock, AR 34.746758333 -92.28876111 Madison, WI 43.074444444 -89.38472222 Montgomery, AL 32.377447222 -86.30094167 Montpelier, VT 44.262222222 -72.58083333 Nashville, TN 36.165833333 -86.78416667 Oklahoma City, OK 35.492280556 -97.50337222 Olympia, WA 47.035277778 -122.9063889 Phoenix, AZ 33.448097222 -112.0970944 Pierre, SD 44.367166667 -100.3463528 Providence, RI 41.830833333 -71.415 Raleigh, NC 35.780277778 -78.63916667 Richmond, VA 37.538758333 -77.43359444 Sacramento, CA 38.576572222 -121.4934111 Saint Paul, MN 44.955147222 -93.10223611 Salem, OR 44.938730556 -123.0300972 Salt Lake City, UT 40.777222222 -111.8880556 Santa Fe, NM 35.682280556 -105.9396583 Springfield, IL 39.798516667 -89.65488889 Tallahassee, FL 30.438111111 -84.2816 Topeka, KS 39.048008333 -95.67815556 Trenton, NJ 40.220436111 -74.76990278 Washington, DC 38.889802778 -77.00911389 ; From this list, you can generate a links data set,  CitiesDist , that contains the distances (in miles) between each pair of cities. The distances are calculated by using the SAS function GEODIST. /* create a list of all the possible pairs of cities */ proc sql; create table CitiesDist as select a.city as city1, a.lat as lat1, a.long as long1, b.city as city2, b.lat as lat2, b.long as long2, geodist(lat1, long1, lat2, long2, 'DM') as distance from Cities as a, Cities as b where a.city < b.city; quit; The following PROC OPTMODEL statements find the optimal tour of all the capital cities: /* find optimal tour by using the network solver */ proc optmodel; set<str,str> CAPPAIRS; set<str> CAPITALS = union {<i,j> in CAPPAIRS} {i,j}; num distance{i in CAPITALS, j in CAPITALS: i < j}; read data CitiesDist into CAPPAIRS=[city1 city2] distance; set<str,str> TOUR; num order{CAPITALS}; solve with NETWORK / loglevel = moderate links = (weight=distance) tsp out = (order=order tour=TOUR) ; put (sum{<i,j> in TOUR} distance[i,j]); /* create tour-ordered pairs (rather than input-ordered pairs) */ str CAPbyOrder{1..card(CAPITALS)}; for {i in CAPITALS} CAPbyOrder[order[i]] = i; set TSPEDGES init setof{i in 2..card(CAPITALS)} <CAPbyOrder[i-1],CAPbyOrder[i]> union {<CAPbyOrder[card(CAPITALS)],CAPbyOrder[1]>}; num distance2{<i,j> in TSPEDGES} = if i < j then distance[i,j] else distance[j,i]; create data TSPTourNodes from [node] tsp_order=order; create data TSPTourLinks from [city1 city2]=TSPEDGES distance=distance2; quit;   ... View more

Hi You can try Black Box Solver for this proplem.   There more information about this method: https://www.youtube.com/watch?v=ODWKUvAT1tY   There examples: https://communities.sas.com/t5/Mathematical-Optimization/SolveBlackBox-Action-Review/m-p/854290#M3829 ... View more

@KevinKalish @Peter7 thanks a lot guys! Hope it will exciting journey! ... View more

Thanks Rob! ... View more

Thanks a lot! It's valuable information! Thought I single enthusiast who research it! I tried it, it's classical LSO and it's working with EM and Forecast Studio Models. But 9.4 doesn't have Python Environment and there is'n opportunity for scoring python models (for example, Catboost or PyTorch NN). Do you have information about it? In this example from Natalia she is using SAS VIYA (i seen mycas library). ... View more