Originally posted by: SystemAdmin
[nadeera said:]
hi!
I'm very new to Cplex and i have not recieved any training on Cplex..Currently i'm trying to apply the column generation technique to a set partitioning problem. The problem is based on SOMBAT et al paper where we're partitioning the set of items into disjoint groups and each group is assigned to a vehicle. No item can be assigned to more than one group (orders cannot be spplit across multiple vehicles) but a supplier can be visited by multiple vehicles (each supplier produces one or more non-identical items).
Since i'm not that good in programming, i'm using the cutstock example (cutstock_int_main.mod) provided, and alter it to fit my problem. My problem would be:
1. [color=blue]masterData.Alpha.add(masterData.Alpha.truck,1,subOpl.z.solutionValue);[/color]
this command is taken straight from the cutstock problem but i changed the variable name accordingly. It is to prepare for the next iteration. When i
try to run it an error occur : [color=red]Scripting runtime error:Wrong component type at position 0, expecting int found float, "undefined".[/color]
i know it is straight forward but even if i change all my var to type int the same problem still occur. So, is it the solving engine or what??
2. [color=blue]for(var i in masterOpl.Items) {
subData.Duals[i] = masterOpl.ctFill[i].dual; }[/color]
I believe this command is to get the dual of the primary problem. Cutstock has only one constraint but mine has 2 constraints. My question is, can we actually named 2 constraints under one label or we only have to use the same command twice with different ctlabel?
3. Another major difference for my problem is that my decision variable is binary (hence the use of boolean for my dvar). So im wondering is it possible for me to use the coding for cutstock n apply it to my inventory problem??
Last but not least, i would appreciate it very much if anyone can show me sample coding for column generation technique (esp those using boolean dvar) on VRP..thank you!!
#DecisionOptimization#OPLusingCPLEXOptimizer