使用Python进行Gurobi线性编程

Question

being so new to Gurobi and optimization. I want to solve this a simple liner model but seems that I made some mistake that I can not detect. so among 3 features which each consumes specific amount of effort to implement I want to select the ones with highest value given a specific capacity. Feature, value, effort f1,3,2 f2,5,1 f3,1,2 capacity = 3

here is my code:

from gurobipy import *
m = Model("C1")    
featuresname, value, effort = multidict({
    "F1":[3,2],
    "F2":[5,1],
    "F3":[1,2]
})
featureset = {}
for f in featuresname:
    featureset[f] = m.addVar(obj=value[f], name=f)
m.modelSense = GRB.MAXIMIZE
m.update()
capacity = 3
m.addConstr(quicksum(effort[f] * featureset[f] for f in featuresname) <=capacity,f)
result = m.optimize()
print(result)
if m.status == GRB.Status.OPTIMAL:
    print('Optimal objective: %g' % m.objVal)
elif m.status != GRB.Status.INFEASIBLE:
    print('Optimization was stopped with status %d' % m.status)

I read all these examples http://www.gurobi.com/resources/examples/example-models-overview but can not find the problem .... can you please give me some hints?

Answer 1

If would be helpful to have a look at the Gurobi output and/or errors you are getting, but just by looking at the code, it seems you forgot to update the model after adding the constraint.

So I would add " m.update() " just before "result = m.optimize()"

Other than that code looks Ok.