We have a case where we must visit 239 locations, for this we have 70 vehicles with a capacity of 750, 2 of the 239 locations have a much higher demand than all the rest, one is 713 and the second is 434.
Entering this into the solver throws an error:
RuntimeError: cuOpt failure at file=/cuopt-build-utilities/cuopt/cpp/src/solution/get_solution.cu line=196: Truck capacity is smaller than volume
Which is not true, since 1 vehicle with a capacity of 750 can carry a demand of 713 and another can carry a demand of 434 (considering that we have 70 vehicles available with no time restrictions or anything extra, only capacity restriction)
This is the only line where a constraint is added:
model.add_capacity_dimension("demand", df['demand'], capacity)
Now, if I remove these two high demands (the one with 713 and 434) from the locations and keep the other 237, whose maximum remains at 214 cuOpt is able to find a solution
How can we solve this situation?